Overview

Brought to you by YData

Dataset statistics

Number of variables122
Number of observations20000
Missing cells592561
Missing cells (%)24.3%
Total size in memory33.0 MiB
Average record size in memory1.7 KiB

Variable types

Numeric106
Text16

Alerts

FLAG_MOBIL has constant value "1" Constant
FLAG_DOCUMENT_10 has constant value "0" Constant
OWN_CAR_AGE has 13243 (66.2%) missing values Missing
OCCUPATION_TYPE has 6278 (31.4%) missing values Missing
EXT_SOURCE_1 has 11328 (56.6%) missing values Missing
EXT_SOURCE_3 has 3937 (19.7%) missing values Missing
APARTMENTS_AVG has 10097 (50.5%) missing values Missing
BASEMENTAREA_AVG has 11714 (58.6%) missing values Missing
YEARS_BEGINEXPLUATATION_AVG has 9707 (48.5%) missing values Missing
YEARS_BUILD_AVG has 13202 (66.0%) missing values Missing
COMMONAREA_AVG has 13918 (69.6%) missing values Missing
ELEVATORS_AVG has 10601 (53.0%) missing values Missing
ENTRANCES_AVG has 10048 (50.2%) missing values Missing
FLOORSMAX_AVG has 9913 (49.6%) missing values Missing
FLOORSMIN_AVG has 13525 (67.6%) missing values Missing
LANDAREA_AVG has 11801 (59.0%) missing values Missing
LIVINGAPARTMENTS_AVG has 13615 (68.1%) missing values Missing
LIVINGAREA_AVG has 9977 (49.9%) missing values Missing
NONLIVINGAPARTMENTS_AVG has 13818 (69.1%) missing values Missing
NONLIVINGAREA_AVG has 10984 (54.9%) missing values Missing
APARTMENTS_MODE has 10097 (50.5%) missing values Missing
BASEMENTAREA_MODE has 11714 (58.6%) missing values Missing
YEARS_BEGINEXPLUATATION_MODE has 9707 (48.5%) missing values Missing
YEARS_BUILD_MODE has 13202 (66.0%) missing values Missing
COMMONAREA_MODE has 13918 (69.6%) missing values Missing
ELEVATORS_MODE has 10601 (53.0%) missing values Missing
ENTRANCES_MODE has 10048 (50.2%) missing values Missing
FLOORSMAX_MODE has 9913 (49.6%) missing values Missing
FLOORSMIN_MODE has 13525 (67.6%) missing values Missing
LANDAREA_MODE has 11801 (59.0%) missing values Missing
LIVINGAPARTMENTS_MODE has 13615 (68.1%) missing values Missing
LIVINGAREA_MODE has 9977 (49.9%) missing values Missing
NONLIVINGAPARTMENTS_MODE has 13818 (69.1%) missing values Missing
NONLIVINGAREA_MODE has 10984 (54.9%) missing values Missing
APARTMENTS_MEDI has 10097 (50.5%) missing values Missing
BASEMENTAREA_MEDI has 11714 (58.6%) missing values Missing
YEARS_BEGINEXPLUATATION_MEDI has 9707 (48.5%) missing values Missing
YEARS_BUILD_MEDI has 13202 (66.0%) missing values Missing
COMMONAREA_MEDI has 13918 (69.6%) missing values Missing
ELEVATORS_MEDI has 10601 (53.0%) missing values Missing
ENTRANCES_MEDI has 10048 (50.2%) missing values Missing
FLOORSMAX_MEDI has 9913 (49.6%) missing values Missing
FLOORSMIN_MEDI has 13525 (67.6%) missing values Missing
LANDAREA_MEDI has 11801 (59.0%) missing values Missing
LIVINGAPARTMENTS_MEDI has 13615 (68.1%) missing values Missing
LIVINGAREA_MEDI has 9977 (49.9%) missing values Missing
NONLIVINGAPARTMENTS_MEDI has 13818 (69.1%) missing values Missing
NONLIVINGAREA_MEDI has 10984 (54.9%) missing values Missing
FONDKAPREMONT_MODE has 13615 (68.1%) missing values Missing
HOUSETYPE_MODE has 9968 (49.8%) missing values Missing
TOTALAREA_MODE has 9596 (48.0%) missing values Missing
WALLSMATERIAL_MODE has 10113 (50.6%) missing values Missing
EMERGENCYSTATE_MODE has 9411 (47.1%) missing values Missing
AMT_REQ_CREDIT_BUREAU_HOUR has 2647 (13.2%) missing values Missing
AMT_REQ_CREDIT_BUREAU_DAY has 2647 (13.2%) missing values Missing
AMT_REQ_CREDIT_BUREAU_WEEK has 2647 (13.2%) missing values Missing
AMT_REQ_CREDIT_BUREAU_MON has 2647 (13.2%) missing values Missing
AMT_REQ_CREDIT_BUREAU_QRT has 2647 (13.2%) missing values Missing
AMT_REQ_CREDIT_BUREAU_YEAR has 2647 (13.2%) missing values Missing
AMT_INCOME_TOTAL is highly skewed (γ1 = 138.6422748) Skewed
FLAG_CONT_MOBILE is highly skewed (γ1 = -22.29521393) Skewed
FLAG_DOCUMENT_2 is highly skewed (γ1 = 70.69476537) Skewed
FLAG_DOCUMENT_4 is highly skewed (γ1 = 99.99249897) Skewed
FLAG_DOCUMENT_7 is highly skewed (γ1 = 81.6374087) Skewed
FLAG_DOCUMENT_12 is highly skewed (γ1 = 141.4213562) Skewed
FLAG_DOCUMENT_15 is highly skewed (γ1 = 24.19348661) Skewed
FLAG_DOCUMENT_17 is highly skewed (γ1 = 49.97374311) Skewed
FLAG_DOCUMENT_19 is highly skewed (γ1 = 37.75958148) Skewed
FLAG_DOCUMENT_20 is highly skewed (γ1 = 39.18791317) Skewed
FLAG_DOCUMENT_21 is highly skewed (γ1 = 47.11215979) Skewed
AMT_REQ_CREDIT_BUREAU_DAY is highly skewed (γ1 = 27.27689465) Skewed
SK_ID_CURR has unique values Unique
TARGET has 18354 (91.8%) zeros Zeros
CNT_CHILDREN has 14013 (70.1%) zeros Zeros
FLAG_EMP_PHONE has 3573 (17.9%) zeros Zeros
FLAG_WORK_PHONE has 15917 (79.6%) zeros Zeros
FLAG_PHONE has 14392 (72.0%) zeros Zeros
FLAG_EMAIL has 18912 (94.6%) zeros Zeros
REG_REGION_NOT_LIVE_REGION has 19697 (98.5%) zeros Zeros
REG_REGION_NOT_WORK_REGION has 18973 (94.9%) zeros Zeros
LIVE_REGION_NOT_WORK_REGION has 19170 (95.9%) zeros Zeros
REG_CITY_NOT_LIVE_CITY has 18475 (92.4%) zeros Zeros
REG_CITY_NOT_WORK_CITY has 15380 (76.9%) zeros Zeros
LIVE_CITY_NOT_WORK_CITY has 16389 (81.9%) zeros Zeros
BASEMENTAREA_AVG has 972 (4.9%) zeros Zeros
COMMONAREA_AVG has 588 (2.9%) zeros Zeros
ELEVATORS_AVG has 5563 (27.8%) zeros Zeros
FLOORSMAX_AVG has 219 (1.1%) zeros Zeros
LANDAREA_AVG has 1032 (5.2%) zeros Zeros
NONLIVINGAPARTMENTS_AVG has 3608 (18.0%) zeros Zeros
NONLIVINGAREA_AVG has 3864 (19.3%) zeros Zeros
BASEMENTAREA_MODE has 1106 (5.5%) zeros Zeros
COMMONAREA_MODE has 669 (3.3%) zeros Zeros
ELEVATORS_MODE has 5834 (29.2%) zeros Zeros
FLOORSMAX_MODE has 250 (1.2%) zeros Zeros
LANDAREA_MODE has 1158 (5.8%) zeros Zeros
NONLIVINGAPARTMENTS_MODE has 3903 (19.5%) zeros Zeros
NONLIVINGAREA_MODE has 4419 (22.1%) zeros Zeros
BASEMENTAREA_MEDI has 984 (4.9%) zeros Zeros
COMMONAREA_MEDI has 604 (3.0%) zeros Zeros
ELEVATORS_MEDI has 5651 (28.3%) zeros Zeros
FLOORSMAX_MEDI has 223 (1.1%) zeros Zeros
LANDAREA_MEDI has 1056 (5.3%) zeros Zeros
NONLIVINGAPARTMENTS_MEDI has 3706 (18.5%) zeros Zeros
NONLIVINGAREA_MEDI has 4001 (20.0%) zeros Zeros
OBS_30_CNT_SOCIAL_CIRCLE has 10690 (53.4%) zeros Zeros
DEF_30_CNT_SOCIAL_CIRCLE has 17625 (88.1%) zeros Zeros
OBS_60_CNT_SOCIAL_CIRCLE has 10742 (53.7%) zeros Zeros
DEF_60_CNT_SOCIAL_CIRCLE has 18223 (91.1%) zeros Zeros
DAYS_LAST_PHONE_CHANGE has 2477 (12.4%) zeros Zeros
FLAG_DOCUMENT_2 has 19996 (> 99.9%) zeros Zeros
FLAG_DOCUMENT_3 has 5830 (29.1%) zeros Zeros
FLAG_DOCUMENT_4 has 19998 (> 99.9%) zeros Zeros
FLAG_DOCUMENT_5 has 19721 (98.6%) zeros Zeros
FLAG_DOCUMENT_6 has 18245 (91.2%) zeros Zeros
FLAG_DOCUMENT_7 has 19997 (> 99.9%) zeros Zeros
FLAG_DOCUMENT_8 has 18331 (91.7%) zeros Zeros
FLAG_DOCUMENT_9 has 19916 (99.6%) zeros Zeros
FLAG_DOCUMENT_10 has 20000 (100.0%) zeros Zeros
FLAG_DOCUMENT_11 has 19909 (99.5%) zeros Zeros
FLAG_DOCUMENT_12 has 19999 (> 99.9%) zeros Zeros
FLAG_DOCUMENT_13 has 19928 (99.6%) zeros Zeros
FLAG_DOCUMENT_14 has 19938 (99.7%) zeros Zeros
FLAG_DOCUMENT_15 has 19966 (99.8%) zeros Zeros
FLAG_DOCUMENT_16 has 19788 (98.9%) zeros Zeros
FLAG_DOCUMENT_17 has 19992 (> 99.9%) zeros Zeros
FLAG_DOCUMENT_18 has 19836 (99.2%) zeros Zeros
FLAG_DOCUMENT_19 has 19986 (99.9%) zeros Zeros
FLAG_DOCUMENT_20 has 19987 (99.9%) zeros Zeros
FLAG_DOCUMENT_21 has 19991 (> 99.9%) zeros Zeros
AMT_REQ_CREDIT_BUREAU_HOUR has 17240 (86.2%) zeros Zeros
AMT_REQ_CREDIT_BUREAU_DAY has 17237 (86.2%) zeros Zeros
AMT_REQ_CREDIT_BUREAU_WEEK has 16794 (84.0%) zeros Zeros
AMT_REQ_CREDIT_BUREAU_MON has 14440 (72.2%) zeros Zeros
AMT_REQ_CREDIT_BUREAU_QRT has 14123 (70.6%) zeros Zeros
AMT_REQ_CREDIT_BUREAU_YEAR has 4823 (24.1%) zeros Zeros

Reproduction

Analysis started2025-09-14 11:08:49.954474
Analysis finished2025-09-14 11:08:52.069345
Duration2.11 seconds
Software versionydata-profiling vv4.16.1
Download configurationconfig.json

Variables

SK_ID_CURR
Real number (ℝ)

Unique 

Distinct20000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean278489.4597
Minimum100002
Maximum456247
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:08:52.698115image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum100002
5-th percentile118845.1
Q1190206
median278652.5
Q3367173
95-th percentile438520.2
Maximum456247
Range356245
Interquartile range (IQR)176967

Descriptive statistics

Standard deviation102316.5495
Coefficient of variation (CV)0.3673982835
Kurtosis-1.187876486
Mean278489.4597
Median Absolute Deviation (MAD)88475.5
Skewness-0.0003220436922
Sum5569789195
Variance1.04686763 × 1010
MonotonicityNot monotonic
2025-09-14T08:08:52.806527image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
223544 1
 
< 0.1%
166120 1
 
< 0.1%
392948 1
 
< 0.1%
441950 1
 
< 0.1%
321020 1
 
< 0.1%
319589 1
 
< 0.1%
203168 1
 
< 0.1%
138284 1
 
< 0.1%
151532 1
 
< 0.1%
264812 1
 
< 0.1%
Other values (19990) 19990
> 99.9%
ValueCountFrequency (%)
100002 1
< 0.1%
100004 1
< 0.1%
100020 1
< 0.1%
100029 1
< 0.1%
100035 1
< 0.1%
ValueCountFrequency (%)
456247 1
< 0.1%
456238 1
< 0.1%
456228 1
< 0.1%
456142 1
< 0.1%
456117 1
< 0.1%

TARGET
Real number (ℝ)

Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0823
Minimum0
Maximum1
Zeros18354
Zeros (%)91.8%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:08:52.887399image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.2748281036
Coefficient of variation (CV)3.339345123
Kurtosis7.242459483
Mean0.0823
Median Absolute Deviation (MAD)0
Skewness3.040022245
Sum1646
Variance0.07553048652
MonotonicityNot monotonic
2025-09-14T08:08:52.958500image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 18354
91.8%
1 1646
 
8.2%
ValueCountFrequency (%)
0 18354
91.8%
1 1646
 
8.2%
ValueCountFrequency (%)
1 1646
 
8.2%
0 18354
91.8%

NAME_CONTRACT_TYPE
Text

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.3 MiB
2025-09-14T08:08:53.146053image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length15
Median length10
Mean length10.47325
Min length10

Characters and Unicode

Total characters209465
Distinct characters13
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowCash loans
2nd rowCash loans
3rd rowCash loans
4th rowCash loans
5th rowCash loans
ValueCountFrequency (%)
loans 20000
50.0%
cash 18107
45.3%
revolving 1893
 
4.7%
2025-09-14T08:08:53.927416image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 38107
18.2%
s 38107
18.2%
n 21893
10.5%
o 21893
10.5%
l 21893
10.5%
20000
9.5%
C 18107
8.6%
h 18107
8.6%
v 3786
 
1.8%
R 1893
 
0.9%
Other values (3) 5679
 
2.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 209465
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 38107
18.2%
s 38107
18.2%
n 21893
10.5%
o 21893
10.5%
l 21893
10.5%
20000
9.5%
C 18107
8.6%
h 18107
8.6%
v 3786
 
1.8%
R 1893
 
0.9%
Other values (3) 5679
 
2.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 209465
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 38107
18.2%
s 38107
18.2%
n 21893
10.5%
o 21893
10.5%
l 21893
10.5%
20000
9.5%
C 18107
8.6%
h 18107
8.6%
v 3786
 
1.8%
R 1893
 
0.9%
Other values (3) 5679
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 209465
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 38107
18.2%
s 38107
18.2%
n 21893
10.5%
o 21893
10.5%
l 21893
10.5%
20000
9.5%
C 18107
8.6%
h 18107
8.6%
v 3786
 
1.8%
R 1893
 
0.9%
Other values (3) 5679
 
2.7%

CODE_GENDER
Text

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.1 MiB
2025-09-14T08:08:53.990640image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters20000
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowM
2nd rowF
3rd rowF
4th rowF
5th rowM
ValueCountFrequency (%)
f 13251
66.3%
m 6749
33.7%
2025-09-14T08:08:54.121399image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
F 13251
66.3%
M 6749
33.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 20000
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
F 13251
66.3%
M 6749
33.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 20000
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
F 13251
66.3%
M 6749
33.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 20000
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
F 13251
66.3%
M 6749
33.7%

FLAG_OWN_CAR
Text

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.1 MiB
2025-09-14T08:08:54.184163image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters20000
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowY
2nd rowY
3rd rowY
4th rowN
5th rowN
ValueCountFrequency (%)
n 13243
66.2%
y 6757
33.8%
2025-09-14T08:08:54.326898image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 13243
66.2%
Y 6757
33.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 20000
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
N 13243
66.2%
Y 6757
33.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 20000
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
N 13243
66.2%
Y 6757
33.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 20000
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
N 13243
66.2%
Y 6757
33.8%

FLAG_OWN_REALTY
Text

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.1 MiB
2025-09-14T08:08:54.379756image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters20000
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowN
2nd rowY
3rd rowN
4th rowY
5th rowY
ValueCountFrequency (%)
y 13652
68.3%
n 6348
31.7%
2025-09-14T08:08:54.492559image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Y 13652
68.3%
N 6348
31.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 20000
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
Y 13652
68.3%
N 6348
31.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 20000
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
Y 13652
68.3%
N 6348
31.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 20000
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
Y 13652
68.3%
N 6348
31.7%

CNT_CHILDREN
Real number (ℝ)

Zeros 

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.41995
Minimum0
Maximum7
Zeros14013
Zeros (%)70.1%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:08:54.552236image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile2
Maximum7
Range7
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.7263734428
Coefficient of variation (CV)1.729666491
Kurtosis3.130701665
Mean0.41995
Median Absolute Deviation (MAD)0
Skewness1.789975722
Sum8399
Variance0.5276183784
MonotonicityNot monotonic
2025-09-14T08:08:54.620551image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 14013
70.1%
1 3939
 
19.7%
2 1735
 
8.7%
3 272
 
1.4%
4 33
 
0.2%
5 7
 
< 0.1%
7 1
 
< 0.1%
ValueCountFrequency (%)
0 14013
70.1%
1 3939
 
19.7%
2 1735
 
8.7%
3 272
 
1.4%
4 33
 
0.2%
ValueCountFrequency (%)
7 1
 
< 0.1%
5 7
 
< 0.1%
4 33
 
0.2%
3 272
 
1.4%
2 1735
8.7%

AMT_INCOME_TOTAL
Real number (ℝ)

Skewed 

Distinct452
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean173589.4335
Minimum27000
Maximum117000000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:08:54.731588image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum27000
5-th percentile67500
Q1112500
median146250
Q3202500
95-th percentile337500
Maximum117000000
Range116973000
Interquartile range (IQR)90000

Descriptive statistics

Standard deviation831622.8467
Coefficient of variation (CV)4.790745783
Kurtosis19476.62781
Mean173589.4335
Median Absolute Deviation (MAD)47250
Skewness138.6422748
Sum3471788671
Variance6.915965591 × 1011
MonotonicityNot monotonic
2025-09-14T08:08:54.860209image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
135000 2318
 
11.6%
112500 2017
 
10.1%
157500 1757
 
8.8%
180000 1544
 
7.7%
90000 1445
 
7.2%
225000 1339
 
6.7%
202500 1063
 
5.3%
67500 744
 
3.7%
270000 716
 
3.6%
81000 395
 
2.0%
Other values (442) 6662
33.3%
ValueCountFrequency (%)
27000 6
< 0.1%
28350 1
 
< 0.1%
31500 12
0.1%
32400 2
 
< 0.1%
32850 1
 
< 0.1%
ValueCountFrequency (%)
117000000 1
< 0.1%
2250000 1
< 0.1%
2025000 1
< 0.1%
1755000 1
< 0.1%
1575000 2
< 0.1%

AMT_CREDIT
Real number (ℝ)

Distinct2427
Distinct (%)12.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean596237.0803
Minimum45000
Maximum4050000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:08:54.983248image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum45000
5-th percentile137538
Q1270000
median508500
Q3808650
95-th percentile1350000
Maximum4050000
Range4005000
Interquartile range (IQR)538650

Descriptive statistics

Standard deviation401924.5855
Coefficient of variation (CV)0.6741019617
Kurtosis2.426508104
Mean596237.0803
Median Absolute Deviation (MAD)247860
Skewness1.305688938
Sum1.192474161 × 1010
Variance1.615433724 × 1011
MonotonicityNot monotonic
2025-09-14T08:08:55.097392image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
450000 680
 
3.4%
675000 560
 
2.8%
225000 525
 
2.6%
270000 489
 
2.4%
180000 462
 
2.3%
900000 418
 
2.1%
545040 302
 
1.5%
254700 281
 
1.4%
135000 248
 
1.2%
808650 247
 
1.2%
Other values (2417) 15788
78.9%
ValueCountFrequency (%)
45000 18
0.1%
47970 17
0.1%
50940 31
0.2%
52128 7
 
< 0.1%
52767 3
 
< 0.1%
ValueCountFrequency (%)
4050000 1
< 0.1%
3600000 1
< 0.1%
3312162 1
< 0.1%
3299688 1
< 0.1%
3150000 1
< 0.1%

AMT_ANNUITY
Real number (ℝ)

Distinct6078
Distinct (%)30.4%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean27070.82207
Minimum1980
Maximum230161.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:08:55.209797image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1980
5-th percentile9000
Q116562.25
median24880.5
Q334546.5
95-th percentile53124.3
Maximum230161.5
Range228181.5
Interquartile range (IQR)17984.25

Descriptive statistics

Standard deviation14613.80171
Coefficient of variation (CV)0.5398359044
Kurtosis10.5392184
Mean27070.82207
Median Absolute Deviation (MAD)8725.5
Skewness1.789448041
Sum541389370.5
Variance213563200.5
MonotonicityNot monotonic
2025-09-14T08:08:55.319199image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9000 403
 
2.0%
13500 364
 
1.8%
6750 167
 
0.8%
10125 128
 
0.6%
12375 110
 
0.5%
20250 101
 
0.5%
37800 94
 
0.5%
22500 90
 
0.4%
26217 89
 
0.4%
11250 84
 
0.4%
Other values (6068) 18369
91.8%
ValueCountFrequency (%)
1980 1
< 0.1%
2542.5 1
< 0.1%
2857.5 1
< 0.1%
3051 1
< 0.1%
3114 1
< 0.1%
ValueCountFrequency (%)
230161.5 1
< 0.1%
225000 1
< 0.1%
220297.5 1
< 0.1%
213291 1
< 0.1%
173574 1
< 0.1%

AMT_GOODS_PRICE
Real number (ℝ)

Distinct429
Distinct (%)2.1%
Missing20
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean535499.0743
Minimum45000
Maximum4050000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:08:55.431627image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum45000
5-th percentile135000
Q1238500
median450000
Q3679500
95-th percentile1305000
Maximum4050000
Range4005000
Interquartile range (IQR)441000

Descriptive statistics

Standard deviation368551.7324
Coefficient of variation (CV)0.6882397189
Kurtosis3.032093129
Mean535499.0743
Median Absolute Deviation (MAD)225000
Skewness1.424247763
Sum1.06992715 × 1010
Variance1.358303794 × 1011
MonotonicityNot monotonic
2025-09-14T08:08:55.544024image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
450000 1837
 
9.2%
225000 1617
 
8.1%
675000 1586
 
7.9%
900000 988
 
4.9%
270000 748
 
3.7%
180000 648
 
3.2%
454500 580
 
2.9%
1125000 568
 
2.8%
135000 531
 
2.7%
315000 311
 
1.6%
Other values (419) 10566
52.8%
ValueCountFrequency (%)
45000 83
0.4%
49500 11
 
0.1%
54000 12
 
0.1%
58500 16
 
0.1%
63000 12
 
0.1%
ValueCountFrequency (%)
4050000 1
 
< 0.1%
3600000 1
 
< 0.1%
3150000 3
< 0.1%
2961000 1
 
< 0.1%
2700000 2
< 0.1%

NAME_TYPE_SUITE
Text

Distinct7
Distinct (%)< 0.1%
Missing83
Missing (%)0.4%
Memory size1.3 MiB
2025-09-14T08:08:55.726253image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length15
Median length13
Mean length12.05372295
Min length6

Characters and Unicode

Total characters240074
Distinct characters28
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUnaccompanied
2nd rowUnaccompanied
3rd rowUnaccompanied
4th rowUnaccompanied
5th rowUnaccompanied
ValueCountFrequency (%)
unaccompanied 16215
78.5%
family 2605
 
12.6%
spouse 706
 
3.4%
partner 706
 
3.4%
children 210
 
1.0%
other_b 126
 
0.6%
other_a 41
 
0.2%
group 14
 
0.1%
of 14
 
0.1%
people 14
 
0.1%
2025-09-14T08:08:56.024630image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 35741
14.9%
n 33346
13.9%
c 32430
13.5%
i 19030
7.9%
m 18820
7.8%
e 18032
7.5%
p 17669
7.4%
o 16963
7.1%
d 16425
6.8%
U 16215
6.8%
Other values (18) 15403
6.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 240074
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 35741
14.9%
n 33346
13.9%
c 32430
13.5%
i 19030
7.9%
m 18820
7.8%
e 18032
7.5%
p 17669
7.4%
o 16963
7.1%
d 16425
6.8%
U 16215
6.8%
Other values (18) 15403
6.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 240074
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 35741
14.9%
n 33346
13.9%
c 32430
13.5%
i 19030
7.9%
m 18820
7.8%
e 18032
7.5%
p 17669
7.4%
o 16963
7.1%
d 16425
6.8%
U 16215
6.8%
Other values (18) 15403
6.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 240074
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 35741
14.9%
n 33346
13.9%
c 32430
13.5%
i 19030
7.9%
m 18820
7.8%
e 18032
7.5%
p 17669
7.4%
o 16963
7.1%
d 16425
6.8%
U 16215
6.8%
Other values (18) 15403
6.4%

NAME_INCOME_TYPE
Text

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.3 MiB
2025-09-14T08:08:56.165780image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length20
Median length7
Mean length10.76005
Min length7

Characters and Unicode

Total characters215201
Distinct characters24
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st rowCommercial associate
2nd rowCommercial associate
3rd rowWorking
4th rowState servant
5th rowWorking
ValueCountFrequency (%)
working 10427
40.1%
commercial 4581
17.6%
associate 4581
17.6%
pensioner 3573
 
13.7%
state 1415
 
5.4%
servant 1415
 
5.4%
student 2
 
< 0.1%
maternity 1
 
< 0.1%
leave 1
 
< 0.1%
businessman 1
 
< 0.1%
2025-09-14T08:08:56.471809image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 23164
10.8%
o 23162
10.8%
r 19997
9.3%
e 19144
 
8.9%
n 18993
 
8.8%
a 16576
 
7.7%
s 14153
 
6.6%
k 10427
 
4.8%
W 10427
 
4.8%
g 10427
 
4.8%
Other values (14) 48731
22.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 215201
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i 23164
10.8%
o 23162
10.8%
r 19997
9.3%
e 19144
 
8.9%
n 18993
 
8.8%
a 16576
 
7.7%
s 14153
 
6.6%
k 10427
 
4.8%
W 10427
 
4.8%
g 10427
 
4.8%
Other values (14) 48731
22.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 215201
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i 23164
10.8%
o 23162
10.8%
r 19997
9.3%
e 19144
 
8.9%
n 18993
 
8.8%
a 16576
 
7.7%
s 14153
 
6.6%
k 10427
 
4.8%
W 10427
 
4.8%
g 10427
 
4.8%
Other values (14) 48731
22.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 215201
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i 23164
10.8%
o 23162
10.8%
r 19997
9.3%
e 19144
 
8.9%
n 18993
 
8.8%
a 16576
 
7.7%
s 14153
 
6.6%
k 10427
 
4.8%
W 10427
 
4.8%
g 10427
 
4.8%
Other values (14) 48731
22.6%

NAME_EDUCATION_TYPE
Text

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.6 MiB
2025-09-14T08:08:56.631018image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length29
Median length29
Mean length25.25015
Min length15

Characters and Unicode

Total characters505003
Distinct characters25
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSecondary / secondary special
2nd rowHigher education
3rd rowSecondary / secondary special
4th rowSecondary / secondary special
5th rowSecondary / secondary special
ValueCountFrequency (%)
secondary 28616
41.8%
14196
20.8%
special 14196
20.8%
higher 5564
 
8.1%
education 4869
 
7.1%
incomplete 695
 
1.0%
lower 224
 
0.3%
academic 16
 
< 0.1%
degree 16
 
< 0.1%
2025-09-14T08:08:57.000889image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 54923
10.9%
c 48408
9.6%
48392
9.6%
a 47697
9.4%
r 34420
 
6.8%
o 34404
 
6.8%
n 34180
 
6.8%
d 33517
 
6.6%
y 28616
 
5.7%
s 28616
 
5.7%
Other values (15) 111830
22.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 505003
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 54923
10.9%
c 48408
9.6%
48392
9.6%
a 47697
9.4%
r 34420
 
6.8%
o 34404
 
6.8%
n 34180
 
6.8%
d 33517
 
6.6%
y 28616
 
5.7%
s 28616
 
5.7%
Other values (15) 111830
22.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 505003
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 54923
10.9%
c 48408
9.6%
48392
9.6%
a 47697
9.4%
r 34420
 
6.8%
o 34404
 
6.8%
n 34180
 
6.8%
d 33517
 
6.6%
y 28616
 
5.7%
s 28616
 
5.7%
Other values (15) 111830
22.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 505003
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 54923
10.9%
c 48408
9.6%
48392
9.6%
a 47697
9.4%
r 34420
 
6.8%
o 34404
 
6.8%
n 34180
 
6.8%
d 33517
 
6.6%
y 28616
 
5.7%
s 28616
 
5.7%
Other values (15) 111830
22.1%

NAME_FAMILY_STATUS
Text

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.3 MiB
2025-09-14T08:08:57.135990image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length20
Median length7
Mean length9.61415
Min length5

Characters and Unicode

Total characters192283
Distinct characters22
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowMarried
2nd rowSingle / not married
3rd rowMarried
4th rowWidow
5th rowSingle / not married
ValueCountFrequency (%)
married 15688
50.9%
single 2957
 
9.6%
2957
 
9.6%
not 2957
 
9.6%
civil 1924
 
6.2%
marriage 1924
 
6.2%
separated 1287
 
4.2%
widow 1100
 
3.6%
unknown 1
 
< 0.1%
2025-09-14T08:08:57.386265image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
r 36511
19.0%
i 25517
13.3%
e 23143
12.0%
a 22110
11.5%
d 18075
9.4%
M 12731
 
6.6%
10795
 
5.6%
n 5917
 
3.1%
l 4881
 
2.5%
g 4881
 
2.5%
Other values (12) 27722
14.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 192283
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
r 36511
19.0%
i 25517
13.3%
e 23143
12.0%
a 22110
11.5%
d 18075
9.4%
M 12731
 
6.6%
10795
 
5.6%
n 5917
 
3.1%
l 4881
 
2.5%
g 4881
 
2.5%
Other values (12) 27722
14.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 192283
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
r 36511
19.0%
i 25517
13.3%
e 23143
12.0%
a 22110
11.5%
d 18075
9.4%
M 12731
 
6.6%
10795
 
5.6%
n 5917
 
3.1%
l 4881
 
2.5%
g 4881
 
2.5%
Other values (12) 27722
14.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 192283
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
r 36511
19.0%
i 25517
13.3%
e 23143
12.0%
a 22110
11.5%
d 18075
9.4%
M 12731
 
6.6%
10795
 
5.6%
n 5917
 
3.1%
l 4881
 
2.5%
g 4881
 
2.5%
Other values (12) 27722
14.4%

NAME_HOUSING_TYPE
Text

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.4 MiB
2025-09-14T08:08:57.534854image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length19
Median length17
Mean length16.79785
Min length12

Characters and Unicode

Total characters335957
Distinct characters25
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowHouse / apartment
2nd rowHouse / apartment
3rd rowHouse / apartment
4th rowHouse / apartment
5th rowHouse / apartment
ValueCountFrequency (%)
apartment 19004
33.0%
house 17669
30.6%
17669
30.6%
with 996
 
1.7%
parents 996
 
1.7%
municipal 777
 
1.3%
rented 329
 
0.6%
office 170
 
0.3%
co-op 59
 
0.1%
2025-09-14T08:08:57.845524image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 40329
12.0%
a 39781
11.8%
e 38497
11.5%
37669
11.2%
n 21106
 
6.3%
p 20836
 
6.2%
r 20000
 
6.0%
m 19004
 
5.7%
s 18665
 
5.6%
u 18446
 
5.5%
Other values (15) 61624
18.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 335957
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
t 40329
12.0%
a 39781
11.8%
e 38497
11.5%
37669
11.2%
n 21106
 
6.3%
p 20836
 
6.2%
r 20000
 
6.0%
m 19004
 
5.7%
s 18665
 
5.6%
u 18446
 
5.5%
Other values (15) 61624
18.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 335957
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
t 40329
12.0%
a 39781
11.8%
e 38497
11.5%
37669
11.2%
n 21106
 
6.3%
p 20836
 
6.2%
r 20000
 
6.0%
m 19004
 
5.7%
s 18665
 
5.6%
u 18446
 
5.5%
Other values (15) 61624
18.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 335957
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
t 40329
12.0%
a 39781
11.8%
e 38497
11.5%
37669
11.2%
n 21106
 
6.3%
p 20836
 
6.2%
r 20000
 
6.0%
m 19004
 
5.7%
s 18665
 
5.6%
u 18446
 
5.5%
Other values (15) 61624
18.3%

REGION_POPULATION_RELATIVE
Real number (ℝ)

Distinct80
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.02089090635
Minimum0.000533
Maximum0.072508
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:08:57.935705image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.000533
5-th percentile0.00496
Q10.010006
median0.01885
Q30.028663
95-th percentile0.04622
Maximum0.072508
Range0.071975
Interquartile range (IQR)0.018657

Descriptive statistics

Standard deviation0.01395070616
Coefficient of variation (CV)0.6677884591
Kurtosis3.269992294
Mean0.02089090635
Median Absolute Deviation (MAD)0.009193
Skewness1.496240327
Sum417.818127
Variance0.0001946222024
MonotonicityNot monotonic
2025-09-14T08:08:58.047432image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.035792 1101
 
5.5%
0.04622 848
 
4.2%
0.026392 769
 
3.8%
0.030755 769
 
3.8%
0.025164 765
 
3.8%
0.031329 742
 
3.7%
0.028663 727
 
3.6%
0.072508 572
 
2.9%
0.019101 565
 
2.8%
0.020713 527
 
2.6%
Other values (70) 12615
63.1%
ValueCountFrequency (%)
0.000533 5
 
< 0.1%
0.000938 1
 
< 0.1%
0.001276 31
0.2%
0.001333 14
0.1%
0.001417 31
0.2%
ValueCountFrequency (%)
0.072508 572
2.9%
0.04622 848
4.2%
0.035792 1101
5.5%
0.032561 414
 
2.1%
0.031329 742
3.7%

DAYS_BIRTH
Real number (ℝ)

Distinct11468
Distinct (%)57.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-16036.3914
Minimum-25197
Maximum-7694
Zeros0
Zeros (%)0.0%
Negative20000
Negative (%)100.0%
Memory size312.5 KiB
2025-09-14T08:08:58.148655image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-25197
5-th percentile-23202.05
Q1-19647.25
median-15745.5
Q3-12382
95-th percentile-9413
Maximum-7694
Range17503
Interquartile range (IQR)7265.25

Descriptive statistics

Standard deviation4372.107907
Coefficient of variation (CV)-0.2726366424
Kurtosis-1.053570859
Mean-16036.3914
Median Absolute Deviation (MAD)3616.5
Skewness-0.120520582
Sum-320727828
Variance19115327.55
MonotonicityNot monotonic
2025-09-14T08:08:58.257003image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-15517 9
 
< 0.1%
-14774 8
 
< 0.1%
-15452 8
 
< 0.1%
-13651 7
 
< 0.1%
-13191 7
 
< 0.1%
-11566 7
 
< 0.1%
-21878 7
 
< 0.1%
-20960 7
 
< 0.1%
-13427 7
 
< 0.1%
-19864 6
 
< 0.1%
Other values (11458) 19927
99.6%
ValueCountFrequency (%)
-25197 1
< 0.1%
-25175 1
< 0.1%
-25161 1
< 0.1%
-25150 1
< 0.1%
-25136 1
< 0.1%
ValueCountFrequency (%)
-7694 1
< 0.1%
-7698 1
< 0.1%
-7706 1
< 0.1%
-7708 1
< 0.1%
-7715 1
< 0.1%

DAYS_EMPLOYED
Real number (ℝ)

Distinct5849
Distinct (%)29.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean63299.72545
Minimum-16607
Maximum365243
Zeros0
Zeros (%)0.0%
Negative16427
Negative (%)82.1%
Memory size312.5 KiB
2025-09-14T08:08:58.367692image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-16607
5-th percentile-6709.3
Q1-2763
median-1203
Q3-290
95-th percentile365243
Maximum365243
Range381850
Interquartile range (IQR)2473

Descriptive statistics

Standard deviation140838.9049
Coefficient of variation (CV)2.224952856
Kurtosis0.8141344431
Mean63299.72545
Median Absolute Deviation (MAD)1084.5
Skewness1.677043709
Sum1265994509
Variance1.983559714 × 1010
MonotonicityNot monotonic
2025-09-14T08:08:58.470338image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
365243 3573
 
17.9%
-214 14
 
0.1%
-287 14
 
0.1%
-321 14
 
0.1%
-222 14
 
0.1%
-118 14
 
0.1%
-116 13
 
0.1%
-385 13
 
0.1%
-194 13
 
0.1%
-201 13
 
0.1%
Other values (5839) 16305
81.5%
ValueCountFrequency (%)
-16607 1
< 0.1%
-16358 1
< 0.1%
-16352 1
< 0.1%
-16113 1
< 0.1%
-15629 1
< 0.1%
ValueCountFrequency (%)
365243 3573
17.9%
-9 1
 
< 0.1%
-11 1
 
< 0.1%
-12 2
 
< 0.1%
-13 2
 
< 0.1%

DAYS_REGISTRATION
Real number (ℝ)

Distinct9672
Distinct (%)48.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-4989.3656
Minimum-24672
Maximum0
Zeros6
Zeros (%)< 0.1%
Negative19994
Negative (%)> 99.9%
Memory size312.5 KiB
2025-09-14T08:08:58.581525image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-24672
5-th percentile-11420.15
Q1-7483
median-4496
Q3-1991.75
95-th percentile-326.95
Maximum0
Range24672
Interquartile range (IQR)5491.25

Descriptive statistics

Standard deviation3539.292795
Coefficient of variation (CV)-0.7093672981
Kurtosis-0.2630415981
Mean-4989.3656
Median Absolute Deviation (MAD)2692
Skewness-0.6080860985
Sum-99787312
Variance12526593.49
MonotonicityNot monotonic
2025-09-14T08:08:58.690058image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-4 10
 
0.1%
-2972 9
 
< 0.1%
-779 9
 
< 0.1%
-944 9
 
< 0.1%
-956 8
 
< 0.1%
-4452 8
 
< 0.1%
-4778 8
 
< 0.1%
-283 8
 
< 0.1%
-769 8
 
< 0.1%
-1107 8
 
< 0.1%
Other values (9662) 19915
99.6%
ValueCountFrequency (%)
-24672 1
< 0.1%
-22392 1
< 0.1%
-20452 1
< 0.1%
-18660 1
< 0.1%
-18572 1
< 0.1%
ValueCountFrequency (%)
0 6
< 0.1%
-1 8
< 0.1%
-2 1
 
< 0.1%
-3 6
< 0.1%
-4 10
0.1%

DAYS_ID_PUBLISH
Real number (ℝ)

Distinct5271
Distinct (%)26.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-2991.751
Minimum-6233
Maximum-1
Zeros0
Zeros (%)0.0%
Negative20000
Negative (%)100.0%
Memory size312.5 KiB
2025-09-14T08:08:58.799812image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-6233
5-th percentile-4932
Q1-4305
median-3247.5
Q3-1729.75
95-th percentile-380
Maximum-1
Range6232
Interquartile range (IQR)2575.25

Descriptive statistics

Standard deviation1507.918306
Coefficient of variation (CV)-0.504025337
Kurtosis-1.116532606
Mean-2991.751
Median Absolute Deviation (MAD)1198
Skewness0.3436469333
Sum-59835020
Variance2273817.618
MonotonicityNot monotonic
2025-09-14T08:08:58.905326image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-4073 23
 
0.1%
-4319 16
 
0.1%
-4495 16
 
0.1%
-4095 16
 
0.1%
-4214 15
 
0.1%
-4749 15
 
0.1%
-4586 15
 
0.1%
-4375 15
 
0.1%
-4285 15
 
0.1%
-4604 15
 
0.1%
Other values (5261) 19839
99.2%
ValueCountFrequency (%)
-6233 1
< 0.1%
-6216 1
< 0.1%
-6197 1
< 0.1%
-6157 1
< 0.1%
-6153 1
< 0.1%
ValueCountFrequency (%)
-1 4
< 0.1%
-2 2
 
< 0.1%
-3 8
< 0.1%
-4 3
 
< 0.1%
-5 6
< 0.1%

OWN_CAR_AGE
Real number (ℝ)

Missing 

Distinct49
Distinct (%)0.7%
Missing13243
Missing (%)66.2%
Infinite0
Infinite (%)0.0%
Mean12.05475803
Minimum0
Maximum65
Zeros136
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:08:59.008584image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q14
median9
Q315
95-th percentile29
Maximum65
Range65
Interquartile range (IQR)11

Descriptive statistics

Standard deviation12.05052603
Coefficient of variation (CV)0.9996489352
Kurtosis9.041823056
Mean12.05475803
Median Absolute Deviation (MAD)5
Skewness2.725186875
Sum81454
Variance145.2151776
MonotonicityNot monotonic
2025-09-14T08:08:59.107229image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
7 469
 
2.3%
3 416
 
2.1%
2 411
 
2.1%
6 410
 
2.1%
8 393
 
2.0%
4 385
 
1.9%
1 347
 
1.7%
9 301
 
1.5%
12 296
 
1.5%
10 295
 
1.5%
Other values (39) 3034
 
15.2%
(Missing) 13243
66.2%
ValueCountFrequency (%)
0 136
 
0.7%
1 347
1.7%
2 411
2.1%
3 416
2.1%
4 385
1.9%
ValueCountFrequency (%)
65 54
 
0.3%
64 168
0.8%
54 1
 
< 0.1%
47 1
 
< 0.1%
45 1
 
< 0.1%

FLAG_MOBIL
Real number (ℝ)

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:08:59.186950image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum20000
Variance0
MonotonicityIncreasing
2025-09-14T08:08:59.236934image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
1 20000
100.0%
ValueCountFrequency (%)
1 20000
100.0%
ValueCountFrequency (%)
1 20000
100.0%

FLAG_EMP_PHONE
Real number (ℝ)

Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.82135
Minimum0
Maximum1
Zeros3573
Zeros (%)17.9%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:08:59.295464image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q31
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.3830685508
Coefficient of variation (CV)0.4663889338
Kurtosis0.8155487032
Mean0.82135
Median Absolute Deviation (MAD)0
Skewness-1.677935386
Sum16427
Variance0.1467415146
MonotonicityNot monotonic
2025-09-14T08:08:59.368217image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
1 16427
82.1%
0 3573
 
17.9%
ValueCountFrequency (%)
0 3573
 
17.9%
1 16427
82.1%
ValueCountFrequency (%)
1 16427
82.1%
0 3573
 
17.9%

FLAG_WORK_PHONE
Real number (ℝ)

Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.20415
Minimum0
Maximum1
Zeros15917
Zeros (%)79.6%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:08:59.437298image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.403089198
Coefficient of variation (CV)1.974475621
Kurtosis0.1552160241
Mean0.20415
Median Absolute Deviation (MAD)0
Skewness1.468060119
Sum4083
Variance0.1624809015
MonotonicityNot monotonic
2025-09-14T08:08:59.494828image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 15917
79.6%
1 4083
 
20.4%
ValueCountFrequency (%)
0 15917
79.6%
1 4083
 
20.4%
ValueCountFrequency (%)
1 4083
 
20.4%
0 15917
79.6%

FLAG_CONT_MOBILE
Real number (ℝ)

Skewed 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.998
Minimum0
Maximum1
Zeros40
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:08:59.562066image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.04467773276
Coefficient of variation (CV)0.0447672673
Kurtosis495.1260768
Mean0.998
Median Absolute Deviation (MAD)0
Skewness-22.29521393
Sum19960
Variance0.001996099805
MonotonicityNot monotonic
2025-09-14T08:08:59.627066image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
1 19960
99.8%
0 40
 
0.2%
ValueCountFrequency (%)
0 40
 
0.2%
1 19960
99.8%
ValueCountFrequency (%)
1 19960
99.8%
0 40
 
0.2%

FLAG_PHONE
Real number (ℝ)

Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.2804
Minimum0
Maximum1
Zeros14392
Zeros (%)72.0%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:08:59.683714image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.4492058874
Coefficient of variation (CV)1.602018143
Kurtosis-1.043966257
Mean0.2804
Median Absolute Deviation (MAD)0
Skewness0.977823169
Sum5608
Variance0.2017859293
MonotonicityNot monotonic
2025-09-14T08:08:59.763441image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 14392
72.0%
1 5608
 
28.0%
ValueCountFrequency (%)
0 14392
72.0%
1 5608
 
28.0%
ValueCountFrequency (%)
1 5608
 
28.0%
0 14392
72.0%

FLAG_EMAIL
Real number (ℝ)

Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0544
Minimum0
Maximum1
Zeros18912
Zeros (%)94.6%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:08:59.829428image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.2268109613
Coefficient of variation (CV)4.169319141
Kurtosis13.44354319
Mean0.0544
Median Absolute Deviation (MAD)0
Skewness3.929656326
Sum1088
Variance0.05144321216
MonotonicityNot monotonic
2025-09-14T08:08:59.899338image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 18912
94.6%
1 1088
 
5.4%
ValueCountFrequency (%)
0 18912
94.6%
1 1088
 
5.4%
ValueCountFrequency (%)
1 1088
 
5.4%
0 18912
94.6%

OCCUPATION_TYPE
Text

Missing 

Distinct18
Distinct (%)0.1%
Missing6278
Missing (%)31.4%
Memory size1.1 MiB
2025-09-14T08:09:00.108376image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length21
Median length20
Mean length10.51792742
Min length7

Characters and Unicode

Total characters144327
Distinct characters36
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSales staff
2nd rowManagers
3rd rowSales staff
4th rowHigh skill tech staff
5th rowLaborers
ValueCountFrequency (%)
staff 6640
30.0%
laborers 3749
17.0%
sales 2112
 
9.6%
core 1817
 
8.2%
managers 1358
 
6.1%
drivers 1201
 
5.4%
high 693
 
3.1%
skill 693
 
3.1%
tech 693
 
3.1%
accountants 657
 
3.0%
Other values (13) 2502
 
11.3%
2025-09-14T08:09:00.470498image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 16926
11.7%
a 16657
11.5%
r 14152
9.8%
e 13744
 
9.5%
f 13280
 
9.2%
t 9493
 
6.6%
8393
 
5.8%
o 7184
 
5.0%
i 5469
 
3.8%
n 4338
 
3.0%
Other values (26) 34691
24.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 144327
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
s 16926
11.7%
a 16657
11.5%
r 14152
9.8%
e 13744
 
9.5%
f 13280
 
9.2%
t 9493
 
6.6%
8393
 
5.8%
o 7184
 
5.0%
i 5469
 
3.8%
n 4338
 
3.0%
Other values (26) 34691
24.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 144327
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
s 16926
11.7%
a 16657
11.5%
r 14152
9.8%
e 13744
 
9.5%
f 13280
 
9.2%
t 9493
 
6.6%
8393
 
5.8%
o 7184
 
5.0%
i 5469
 
3.8%
n 4338
 
3.0%
Other values (26) 34691
24.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 144327
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
s 16926
11.7%
a 16657
11.5%
r 14152
9.8%
e 13744
 
9.5%
f 13280
 
9.2%
t 9493
 
6.6%
8393
 
5.8%
o 7184
 
5.0%
i 5469
 
3.8%
n 4338
 
3.0%
Other values (26) 34691
24.0%

CNT_FAM_MEMBERS
Real number (ℝ)

Distinct8
Distinct (%)< 0.1%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean2.152757638
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:00.548072image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median2
Q33
95-th percentile4
Maximum9
Range8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9180416934
Coefficient of variation (CV)0.4264491633
Kurtosis1.085411911
Mean2.152757638
Median Absolute Deviation (MAD)0
Skewness0.9097953228
Sum43053
Variance0.8428005509
MonotonicityNot monotonic
2025-09-14T08:09:00.775113image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
2 10229
51.1%
1 4481
22.4%
3 3385
 
16.9%
4 1610
 
8.1%
5 255
 
1.3%
6 31
 
0.2%
7 7
 
< 0.1%
9 1
 
< 0.1%
(Missing) 1
 
< 0.1%
ValueCountFrequency (%)
1 4481
22.4%
2 10229
51.1%
3 3385
 
16.9%
4 1610
 
8.1%
5 255
 
1.3%
ValueCountFrequency (%)
9 1
 
< 0.1%
7 7
 
< 0.1%
6 31
 
0.2%
5 255
 
1.3%
4 1610
8.1%

REGION_RATING_CLIENT
Real number (ℝ)

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0527
Minimum1
Maximum3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:00.851145image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median2
Q32
95-th percentile3
Maximum3
Range2
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.5098389028
Coefficient of variation (CV)0.248374776
Kurtosis0.7889217824
Mean2.0527
Median Absolute Deviation (MAD)0
Skewness0.08648591983
Sum41054
Variance0.2599357068
MonotonicityNot monotonic
2025-09-14T08:09:00.930787image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=3)
ValueCountFrequency (%)
2 14746
73.7%
3 3154
 
15.8%
1 2100
 
10.5%
ValueCountFrequency (%)
1 2100
 
10.5%
2 14746
73.7%
3 3154
 
15.8%
ValueCountFrequency (%)
3 3154
 
15.8%
2 14746
73.7%
1 2100
 
10.5%

REGION_RATING_CLIENT_W_CITY
Real number (ℝ)

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0329
Minimum1
Maximum3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:01.049885image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median2
Q32
95-th percentile3
Maximum3
Range2
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.5036171875
Coefficient of variation (CV)0.2477333796
Kurtosis0.9186516839
Mean2.0329
Median Absolute Deviation (MAD)0
Skewness0.0613274119
Sum40658
Variance0.2536302715
MonotonicityNot monotonic
2025-09-14T08:09:01.189697image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=3)
ValueCountFrequency (%)
2 14906
74.5%
3 2876
 
14.4%
1 2218
 
11.1%
ValueCountFrequency (%)
1 2218
 
11.1%
2 14906
74.5%
3 2876
 
14.4%
ValueCountFrequency (%)
3 2876
 
14.4%
2 14906
74.5%
1 2218
 
11.1%

WEEKDAY_APPR_PROCESS_START
Text

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.2 MiB
2025-09-14T08:09:01.421360image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length9
Median length8
Mean length7.22645
Min length6

Characters and Unicode

Total characters144529
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowTHURSDAY
2nd rowTHURSDAY
3rd rowTUESDAY
4th rowFRIDAY
5th rowWEDNESDAY
ValueCountFrequency (%)
tuesday 3433
17.2%
wednesday 3432
17.2%
monday 3294
16.5%
friday 3291
16.5%
thursday 3198
16.0%
saturday 2202
11.0%
sunday 1150
 
5.8%
2025-09-14T08:09:01.770154image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
D 23432
16.2%
A 22202
15.4%
Y 20000
13.8%
S 13415
9.3%
E 10297
7.1%
U 9983
6.9%
T 8833
 
6.1%
R 8691
 
6.0%
N 7876
 
5.4%
W 3432
 
2.4%
Other values (5) 16368
11.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 144529
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
D 23432
16.2%
A 22202
15.4%
Y 20000
13.8%
S 13415
9.3%
E 10297
7.1%
U 9983
6.9%
T 8833
 
6.1%
R 8691
 
6.0%
N 7876
 
5.4%
W 3432
 
2.4%
Other values (5) 16368
11.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 144529
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
D 23432
16.2%
A 22202
15.4%
Y 20000
13.8%
S 13415
9.3%
E 10297
7.1%
U 9983
6.9%
T 8833
 
6.1%
R 8691
 
6.0%
N 7876
 
5.4%
W 3432
 
2.4%
Other values (5) 16368
11.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 144529
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
D 23432
16.2%
A 22202
15.4%
Y 20000
13.8%
S 13415
9.3%
E 10297
7.1%
U 9983
6.9%
T 8833
 
6.1%
R 8691
 
6.0%
N 7876
 
5.4%
W 3432
 
2.4%
Other values (5) 16368
11.3%

HOUR_APPR_PROCESS_START
Real number (ℝ)

Distinct24
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.0602
Minimum0
Maximum23
Zeros3
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:01.847531image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile7
Q110
median12
Q314
95-th percentile17
Maximum23
Range23
Interquartile range (IQR)4

Descriptive statistics

Standard deviation3.263435071
Coefficient of variation (CV)0.2705954355
Kurtosis-0.196861143
Mean12.0602
Median Absolute Deviation (MAD)2
Skewness-0.0009759176179
Sum241204
Variance10.65000846
MonotonicityNot monotonic
2025-09-14T08:09:01.933326image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
10 2535
12.7%
11 2392
12.0%
12 2285
11.4%
13 1996
10.0%
9 1773
8.9%
14 1756
8.8%
15 1559
7.8%
16 1346
6.7%
17 975
 
4.9%
8 961
 
4.8%
Other values (14) 2422
12.1%
ValueCountFrequency (%)
0 3
 
< 0.1%
1 5
 
< 0.1%
2 20
 
0.1%
3 68
0.3%
4 126
0.6%
ValueCountFrequency (%)
23 3
 
< 0.1%
22 10
 
0.1%
21 29
 
0.1%
20 89
 
0.4%
19 252
1.3%

REG_REGION_NOT_LIVE_REGION
Real number (ℝ)

Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.01515
Minimum0
Maximum1
Zeros19697
Zeros (%)98.5%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:02.039001image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.1221524603
Coefficient of variation (CV)8.062868668
Kurtosis61.03754202
Mean0.01515
Median Absolute Deviation (MAD)0
Skewness7.939234111
Sum303
Variance0.01492122356
MonotonicityNot monotonic
2025-09-14T08:09:02.106668image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 19697
98.5%
1 303
 
1.5%
ValueCountFrequency (%)
0 19697
98.5%
1 303
 
1.5%
ValueCountFrequency (%)
1 303
 
1.5%
0 19697
98.5%

REG_REGION_NOT_WORK_REGION
Real number (ℝ)

Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.05135
Minimum0
Maximum1
Zeros18973
Zeros (%)94.9%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:02.169955image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.2207161373
Coefficient of variation (CV)4.298269471
Kurtosis14.53225904
Mean0.05135
Median Absolute Deviation (MAD)0
Skewness4.065809369
Sum1027
Variance0.04871561328
MonotonicityNot monotonic
2025-09-14T08:09:02.242334image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 18973
94.9%
1 1027
 
5.1%
ValueCountFrequency (%)
0 18973
94.9%
1 1027
 
5.1%
ValueCountFrequency (%)
1 1027
 
5.1%
0 18973
94.9%

LIVE_REGION_NOT_WORK_REGION
Real number (ℝ)

Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0415
Minimum0
Maximum1
Zeros19170
Zeros (%)95.9%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:02.315206image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.1994485873
Coefficient of variation (CV)4.805990056
Kurtosis19.1447682
Mean0.0415
Median Absolute Deviation (MAD)0
Skewness4.598135898
Sum830
Variance0.03977973899
MonotonicityNot monotonic
2025-09-14T08:09:02.371408image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 19170
95.9%
1 830
 
4.2%
ValueCountFrequency (%)
0 19170
95.9%
1 830
 
4.2%
ValueCountFrequency (%)
1 830
 
4.2%
0 19170
95.9%

REG_CITY_NOT_LIVE_CITY
Real number (ℝ)

Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.07625
Minimum0
Maximum1
Zeros18475
Zeros (%)92.4%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:02.428338image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.2654043321
Coefficient of variation (CV)3.480712552
Kurtosis8.19964783
Mean0.07625
Median Absolute Deviation (MAD)0
Skewness3.193560376
Sum1525
Variance0.07043945947
MonotonicityNot monotonic
2025-09-14T08:09:02.486871image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 18475
92.4%
1 1525
 
7.6%
ValueCountFrequency (%)
0 18475
92.4%
1 1525
 
7.6%
ValueCountFrequency (%)
1 1525
 
7.6%
0 18475
92.4%

REG_CITY_NOT_WORK_CITY
Real number (ℝ)

Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.231
Minimum0
Maximum1
Zeros15380
Zeros (%)76.9%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:02.550543image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.4214829562
Coefficient of variation (CV)1.824601542
Kurtosis-0.370398162
Mean0.231
Median Absolute Deviation (MAD)0
Skewness1.276573103
Sum4620
Variance0.1776478824
MonotonicityNot monotonic
2025-09-14T08:09:02.615012image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 15380
76.9%
1 4620
 
23.1%
ValueCountFrequency (%)
0 15380
76.9%
1 4620
 
23.1%
ValueCountFrequency (%)
1 4620
 
23.1%
0 15380
76.9%

LIVE_CITY_NOT_WORK_CITY
Real number (ℝ)

Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.18055
Minimum0
Maximum1
Zeros16389
Zeros (%)81.9%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:02.676016image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.3846545144
Coefficient of variation (CV)2.130459786
Kurtosis0.7594525024
Mean0.18055
Median Absolute Deviation (MAD)0
Skewness1.661137131
Sum3611
Variance0.1479590955
MonotonicityNot monotonic
2025-09-14T08:09:02.734437image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 16389
81.9%
1 3611
 
18.1%
ValueCountFrequency (%)
0 16389
81.9%
1 3611
 
18.1%
ValueCountFrequency (%)
1 3611
 
18.1%
0 16389
81.9%

ORGANIZATION_TYPE
Text

Distinct58
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size1.3 MiB
2025-09-14T08:09:02.993486image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length22
Median length17
Mean length12.51455
Min length3

Characters and Unicode

Total characters250291
Distinct characters52
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowBusiness Entity Type 3
2nd rowBusiness Entity Type 3
3rd rowSelf-employed
4th rowBusiness Entity Type 3
5th rowBusiness Entity Type 3
ValueCountFrequency (%)
type 7961
19.2%
business 5464
13.2%
entity 5464
13.2%
3 4942
11.9%
xna 3573
8.6%
self-employed 2520
 
6.1%
other 1110
 
2.7%
2 986
 
2.4%
industry 953
 
2.3%
trade 922
 
2.2%
Other values (40) 7632
18.4%
2025-09-14T08:09:03.339786image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 28364
 
11.3%
21527
 
8.6%
t 19533
 
7.8%
s 19337
 
7.7%
y 17610
 
7.0%
n 17121
 
6.8%
i 15302
 
6.1%
p 11103
 
4.4%
u 7891
 
3.2%
r 7670
 
3.1%
Other values (42) 84833
33.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 250291
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 28364
 
11.3%
21527
 
8.6%
t 19533
 
7.8%
s 19337
 
7.7%
y 17610
 
7.0%
n 17121
 
6.8%
i 15302
 
6.1%
p 11103
 
4.4%
u 7891
 
3.2%
r 7670
 
3.1%
Other values (42) 84833
33.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 250291
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 28364
 
11.3%
21527
 
8.6%
t 19533
 
7.8%
s 19337
 
7.7%
y 17610
 
7.0%
n 17121
 
6.8%
i 15302
 
6.1%
p 11103
 
4.4%
u 7891
 
3.2%
r 7670
 
3.1%
Other values (42) 84833
33.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 250291
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 28364
 
11.3%
21527
 
8.6%
t 19533
 
7.8%
s 19337
 
7.7%
y 17610
 
7.0%
n 17121
 
6.8%
i 15302
 
6.1%
p 11103
 
4.4%
u 7891
 
3.2%
r 7670
 
3.1%
Other values (42) 84833
33.9%

EXT_SOURCE_1
Real number (ℝ)

Missing 

Distinct8583
Distinct (%)99.0%
Missing11328
Missing (%)56.6%
Infinite0
Infinite (%)0.0%
Mean0.5018631536
Minimum0.0150529213
Maximum0.9414327203
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:03.421539image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.0150529213
5-th percentile0.1544652118
Q10.3342909904
median0.5053869785
Q30.6743687206
95-th percentile0.8323072465
Maximum0.9414327203
Range0.926379799
Interquartile range (IQR)0.3400777302

Descriptive statistics

Standard deviation0.2114948595
Coefficient of variation (CV)0.4214193809
Kurtosis-0.9588963382
Mean0.5018631536
Median Absolute Deviation (MAD)0.1697561649
Skewness-0.07337405786
Sum4352.157268
Variance0.0447300756
MonotonicityNot monotonic
2025-09-14T08:09:03.515177image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.3000218043 3
 
< 0.1%
0.3908541244 2
 
< 0.1%
0.4351326632 2
 
< 0.1%
0.6449668361 2
 
< 0.1%
0.3745322567 2
 
< 0.1%
0.4059138791 2
 
< 0.1%
0.4116134473 2
 
< 0.1%
0.7585239866 2
 
< 0.1%
0.1938268284 2
 
< 0.1%
0.7332857261 2
 
< 0.1%
Other values (8573) 8651
43.3%
(Missing) 11328
56.6%
ValueCountFrequency (%)
0.0150529213 1
< 0.1%
0.01560008058 1
< 0.1%
0.02093879214 1
< 0.1%
0.02628923932 1
< 0.1%
0.03107887643 1
< 0.1%
ValueCountFrequency (%)
0.9414327203 1
< 0.1%
0.9381898537 1
< 0.1%
0.9362974713 1
< 0.1%
0.9347469876 1
< 0.1%
0.9328299007 1
< 0.1%

EXT_SOURCE_2
Real number (ℝ)

Distinct17875
Distinct (%)89.6%
Missing41
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean0.5137845377
Minimum5.600337749 × 10-6
Maximum0.8549996664
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:03.610834image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum5.600337749 × 10-6
5-th percentile0.1301516848
Q10.3915687886
median0.5657626607
Q30.6629137936
95-th percentile0.7468967069
Maximum0.8549996664
Range0.8549940661
Interquartile range (IQR)0.2713450051

Descriptive statistics

Standard deviation0.191137089
Coefficient of variation (CV)0.3720179861
Kurtosis-0.2697836042
Mean0.5137845377
Median Absolute Deviation (MAD)0.1183106267
Skewness-0.7972955307
Sum10254.62559
Variance0.03653338679
MonotonicityNot monotonic
2025-09-14T08:09:03.704281image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.2858978721 42
 
0.2%
0.2652563402 29
 
0.1%
0.1596792335 24
 
0.1%
0.2622583692 20
 
0.1%
0.2653117485 19
 
0.1%
0.2665197754 19
 
0.1%
0.1631870355 18
 
0.1%
0.162192106 15
 
0.1%
0.1953537989 14
 
0.1%
0.1621445677 13
 
0.1%
Other values (17865) 19746
98.7%
(Missing) 41
 
0.2%
ValueCountFrequency (%)
5.600337749 × 10-61
< 0.1%
3.485476828 × 10-51
< 0.1%
0.0001353973014 1
< 0.1%
0.0001524220162 1
< 0.1%
0.0002513101075 1
< 0.1%
ValueCountFrequency (%)
0.8549996664 2
< 0.1%
0.8133415671 1
< 0.1%
0.8119732555 1
< 0.1%
0.8118697375 1
< 0.1%
0.8106610299 1
< 0.1%

EXT_SOURCE_3
Real number (ℝ)

Missing 

Distinct694
Distinct (%)4.3%
Missing3937
Missing (%)19.7%
Infinite0
Infinite (%)0.0%
Mean0.5075192204
Minimum0.0005272652387
Maximum0.8802684804
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:03.796463image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.0005272652387
5-th percentile0.151934549
Q10.3672910183
median0.5316861425
Q30.665854922
95-th percentile0.7850520264
Maximum0.8802684804
Range0.8797412151
Interquartile range (IQR)0.2985639037

Descriptive statistics

Standard deviation0.1950287831
Coefficient of variation (CV)0.3842786149
Kurtosis-0.6745828458
Mean0.5075192204
Median Absolute Deviation (MAD)0.1468815462
Skewness-0.3988918025
Sum8152.281238
Variance0.03803622622
MonotonicityNot monotonic
2025-09-14T08:09:03.886475image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.7463002131 96
 
0.5%
0.5549467685 94
 
0.5%
0.7136313997 92
 
0.5%
0.5118918015 78
 
0.4%
0.5814837058 77
 
0.4%
0.6263042767 77
 
0.4%
0.6940926425 76
 
0.4%
0.7062051097 73
 
0.4%
0.740799088 73
 
0.4%
0.665854922 73
 
0.4%
Other values (684) 15254
76.3%
(Missing) 3937
 
19.7%
ValueCountFrequency (%)
0.0005272652387 58
0.3%
0.01394846558 1
 
< 0.1%
0.02372083083 1
 
< 0.1%
0.02388843609 2
 
< 0.1%
0.02581001068 1
 
< 0.1%
ValueCountFrequency (%)
0.8802684804 2
 
< 0.1%
0.878739767 1
 
< 0.1%
0.8771942582 1
 
< 0.1%
0.8667312343 1
 
< 0.1%
0.8658959153 6
< 0.1%

APARTMENTS_AVG
Real number (ℝ)

Missing 

Distinct1016
Distinct (%)10.3%
Missing10097
Missing (%)50.5%
Infinite0
Infinite (%)0.0%
Mean0.117890104
Minimum0
Maximum1
Zeros42
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:03.978076image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0082
Q10.0582
median0.0876
Q30.1485
95-th percentile0.3289
Maximum1
Range1
Interquartile range (IQR)0.0903

Descriptive statistics

Standard deviation0.1075193313
Coefficient of variation (CV)0.9120301674
Kurtosis10.04105561
Mean0.117890104
Median Absolute Deviation (MAD)0.0433
Skewness2.504471279
Sum1167.4657
Variance0.0115604066
MonotonicityNot monotonic
2025-09-14T08:09:04.078596image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0825 426
 
2.1%
0.0619 402
 
2.0%
0.0722 262
 
1.3%
0.0928 259
 
1.3%
0.0082 221
 
1.1%
0.0165 198
 
1.0%
0.1031 191
 
1.0%
0.0124 177
 
0.9%
0.1485 172
 
0.9%
0.0742 168
 
0.8%
Other values (1006) 7427
37.1%
(Missing) 10097
50.5%
ValueCountFrequency (%)
0 42
0.2%
0.001 13
 
0.1%
0.0015 1
 
< 0.1%
0.0021 54
0.3%
0.0026 1
 
< 0.1%
ValueCountFrequency (%)
1 7
< 0.1%
0.9814 1
 
< 0.1%
0.966 1
 
< 0.1%
0.8979 1
 
< 0.1%
0.8825 1
 
< 0.1%

BASEMENTAREA_AVG
Real number (ℝ)

Missing  Zeros 

Distinct2106
Distinct (%)25.4%
Missing11714
Missing (%)58.6%
Infinite0
Infinite (%)0.0%
Mean0.08723350229
Minimum0
Maximum1
Zeros972
Zeros (%)4.9%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:04.172058image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.044
median0.0763
Q30.1117
95-th percentile0.217575
Maximum1
Range1
Interquartile range (IQR)0.0677

Descriptive statistics

Standard deviation0.07979738328
Coefficient of variation (CV)0.9147561565
Kurtosis27.15059098
Mean0.08723350229
Median Absolute Deviation (MAD)0.0339
Skewness3.548869467
Sum722.8168
Variance0.006367622378
MonotonicityNot monotonic
2025-09-14T08:09:04.274012image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 972
 
4.9%
0.0818 22
 
0.1%
0.0625 21
 
0.1%
0.08 20
 
0.1%
0.0796 20
 
0.1%
0.1091 19
 
0.1%
0.0804 19
 
0.1%
0.0803 18
 
0.1%
0.0764 17
 
0.1%
0.0845 16
 
0.1%
Other values (2096) 7142
35.7%
(Missing) 11714
58.6%
ValueCountFrequency (%)
0 972
4.9%
0.0001 4
 
< 0.1%
0.0002 5
 
< 0.1%
0.0005 7
 
< 0.1%
0.0006 2
 
< 0.1%
ValueCountFrequency (%)
1 9
< 0.1%
0.9677 1
 
< 0.1%
0.815 1
 
< 0.1%
0.7924 1
 
< 0.1%
0.7775 1
 
< 0.1%

YEARS_BEGINEXPLUATATION_AVG
Real number (ℝ)

Missing 

Distinct144
Distinct (%)1.4%
Missing9707
Missing (%)48.5%
Infinite0
Infinite (%)0.0%
Mean0.977175459
Minimum0
Maximum1
Zeros38
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:04.376416image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.9685
Q10.9767
median0.9816
Q30.9866
95-th percentile0.9955
Maximum1
Range1
Interquartile range (IQR)0.0099

Descriptive statistics

Standard deviation0.06266078422
Coefficient of variation (CV)0.06412439408
Kurtosis225.0125423
Mean0.977175459
Median Absolute Deviation (MAD)0.005
Skewness-14.80884128
Sum10058.067
Variance0.003926373879
MonotonicityNot monotonic
2025-09-14T08:09:04.475792image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.9871 284
 
1.4%
0.9876 282
 
1.4%
0.9806 280
 
1.4%
0.9821 275
 
1.4%
0.9851 271
 
1.4%
0.9816 271
 
1.4%
0.9831 270
 
1.4%
0.9811 268
 
1.3%
0.9801 266
 
1.3%
0.9856 263
 
1.3%
Other values (134) 7563
37.8%
(Missing) 9707
48.5%
ValueCountFrequency (%)
0 38
0.2%
0.0179 1
 
< 0.1%
0.1987 1
 
< 0.1%
0.4883 1
 
< 0.1%
0.4898 1
 
< 0.1%
ValueCountFrequency (%)
1 11
 
0.1%
0.9995 44
0.2%
0.999 59
0.3%
0.9985 56
0.3%
0.998 66
0.3%

YEARS_BUILD_AVG
Real number (ℝ)

Missing 

Distinct117
Distinct (%)1.7%
Missing13202
Missing (%)66.0%
Infinite0
Infinite (%)0.0%
Mean0.7513026773
Minimum0
Maximum1
Zeros3
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:04.713334image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.592
Q10.6872
median0.7552
Q30.8232
95-th percentile0.9524
Maximum1
Range1
Interquartile range (IQR)0.136

Descriptive statistics

Standard deviation0.1150516685
Coefficient of variation (CV)0.1531362418
Kurtosis3.973267521
Mean0.7513026773
Median Absolute Deviation (MAD)0.068
Skewness-0.9593773097
Sum5107.3556
Variance0.01323688642
MonotonicityNot monotonic
2025-09-14T08:09:04.818232image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.83 206
 
1.0%
0.8232 195
 
1.0%
0.8028 194
 
1.0%
0.796 193
 
1.0%
0.8096 190
 
0.9%
0.7416 186
 
0.9%
0.8164 184
 
0.9%
0.7484 183
 
0.9%
0.7348 177
 
0.9%
0.7688 175
 
0.9%
Other values (107) 4915
 
24.6%
(Missing) 13202
66.0%
ValueCountFrequency (%)
0 3
< 0.1%
0.0004 1
 
< 0.1%
0.0072 1
 
< 0.1%
0.0344 1
 
< 0.1%
0.0548 2
< 0.1%
ValueCountFrequency (%)
1 11
 
0.1%
0.9932 31
0.2%
0.9864 46
0.2%
0.9796 42
0.2%
0.9728 52
0.3%

COMMONAREA_AVG
Real number (ℝ)

Missing  Zeros 

Distinct1394
Distinct (%)22.9%
Missing13918
Missing (%)69.6%
Infinite0
Infinite (%)0.0%
Mean0.04540271292
Minimum0
Maximum1
Zeros588
Zeros (%)2.9%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:04.928898image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.0077
median0.02095
Q30.0507
95-th percentile0.166665
Maximum1
Range1
Interquartile range (IQR)0.043

Descriptive statistics

Standard deviation0.08167181653
Coefficient of variation (CV)1.798831199
Kurtosis44.8478198
Mean0.04540271292
Median Absolute Deviation (MAD)0.01695
Skewness5.570494038
Sum276.1393
Variance0.006670285615
MonotonicityNot monotonic
2025-09-14T08:09:05.035195image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 588
 
2.9%
0.0078 32
 
0.2%
0.0079 29
 
0.1%
0.0069 27
 
0.1%
0.0077 26
 
0.1%
0.0096 25
 
0.1%
0.001 25
 
0.1%
0.0014 24
 
0.1%
0.0094 24
 
0.1%
0.007 23
 
0.1%
Other values (1384) 5259
 
26.3%
(Missing) 13918
69.6%
ValueCountFrequency (%)
0 588
2.9%
0.0001 3
 
< 0.1%
0.0002 3
 
< 0.1%
0.0003 5
 
< 0.1%
0.0004 3
 
< 0.1%
ValueCountFrequency (%)
1 7
< 0.1%
0.9505 1
 
< 0.1%
0.8855 1
 
< 0.1%
0.8808 1
 
< 0.1%
0.877 1
 
< 0.1%

ELEVATORS_AVG
Real number (ℝ)

Missing  Zeros 

Distinct129
Distinct (%)1.4%
Missing10601
Missing (%)53.0%
Infinite0
Infinite (%)0.0%
Mean0.0794571763
Minimum0
Maximum1
Zeros5563
Zeros (%)27.8%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:05.138234image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.12
95-th percentile0.36
Maximum1
Range1
Interquartile range (IQR)0.12

Descriptive statistics

Standard deviation0.1346679856
Coefficient of variation (CV)1.694849878
Kurtosis7.869697463
Mean0.0794571763
Median Absolute Deviation (MAD)0
Skewness2.443712406
Sum746.818
Variance0.01813546633
MonotonicityNot monotonic
2025-09-14T08:09:05.245015image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 5563
27.8%
0.08 677
 
3.4%
0.16 559
 
2.8%
0.24 409
 
2.0%
0.12 392
 
2.0%
0.04 289
 
1.4%
0.2 285
 
1.4%
0.32 186
 
0.9%
0.28 141
 
0.7%
0.36 102
 
0.5%
Other values (119) 796
 
4.0%
(Missing) 10601
53.0%
ValueCountFrequency (%)
0 5563
27.8%
0.008 3
 
< 0.1%
0.01 3
 
< 0.1%
0.0112 1
 
< 0.1%
0.0132 4
 
< 0.1%
ValueCountFrequency (%)
1 7
< 0.1%
0.96 8
< 0.1%
0.92 1
 
< 0.1%
0.88 7
< 0.1%
0.84 3
 
< 0.1%

ENTRANCES_AVG
Real number (ℝ)

Missing 

Distinct142
Distinct (%)1.4%
Missing10048
Missing (%)50.2%
Infinite0
Infinite (%)0.0%
Mean0.1491969453
Minimum0
Maximum1
Zeros20
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:05.347608image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0345
Q10.069
median0.1379
Q30.2069
95-th percentile0.3103
Maximum1
Range1
Interquartile range (IQR)0.1379

Descriptive statistics

Standard deviation0.09947729479
Coefficient of variation (CV)0.6667515515
Kurtosis11.74938229
Mean0.1491969453
Median Absolute Deviation (MAD)0.0689
Skewness2.417000455
Sum1484.808
Variance0.009895732178
MonotonicityNot monotonic
2025-09-14T08:09:05.468125image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.1379 2187
 
10.9%
0.069 1454
 
7.3%
0.1034 1286
 
6.4%
0.2069 1239
 
6.2%
0.0345 1022
 
5.1%
0.1724 641
 
3.2%
0.2759 491
 
2.5%
0.2414 283
 
1.4%
0.3103 136
 
0.7%
0.3448 118
 
0.6%
Other values (132) 1095
 
5.5%
(Missing) 10048
50.2%
ValueCountFrequency (%)
0 20
 
0.1%
0.0114 1
 
< 0.1%
0.0345 1022
5.1%
0.0372 1
 
< 0.1%
0.0383 1
 
< 0.1%
ValueCountFrequency (%)
1 8
< 0.1%
0.9655 2
 
< 0.1%
0.931 1
 
< 0.1%
0.8966 7
< 0.1%
0.8276 3
 
< 0.1%

FLOORSMAX_AVG
Real number (ℝ)

Missing  Zeros 

Distinct157
Distinct (%)1.6%
Missing9913
Missing (%)49.6%
Infinite0
Infinite (%)0.0%
Mean0.227297928
Minimum0
Maximum1
Zeros219
Zeros (%)1.1%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:05.584084image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0417
Q10.1667
median0.1667
Q30.3333
95-th percentile0.5
Maximum1
Range1
Interquartile range (IQR)0.1666

Descriptive statistics

Standard deviation0.1457480644
Coefficient of variation (CV)0.6412203827
Kurtosis2.417104108
Mean0.227297928
Median Absolute Deviation (MAD)0.0834
Skewness1.226159118
Sum2292.7542
Variance0.02124249827
MonotonicityNot monotonic
2025-09-14T08:09:05.684889image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.1667 3986
19.9%
0.3333 2101
 
10.5%
0.0417 929
 
4.6%
0.375 510
 
2.5%
0.125 466
 
2.3%
0.0833 390
 
1.9%
0 219
 
1.1%
0.4583 188
 
0.9%
0.25 137
 
0.7%
0.5417 130
 
0.7%
Other values (147) 1031
 
5.2%
(Missing) 9913
49.6%
ValueCountFrequency (%)
0 219
1.1%
0.0083 1
 
< 0.1%
0.0104 1
 
< 0.1%
0.0138 1
 
< 0.1%
0.0208 7
 
< 0.1%
ValueCountFrequency (%)
1 10
0.1%
0.9583 4
 
< 0.1%
0.9167 2
 
< 0.1%
0.8992 1
 
< 0.1%
0.875 17
0.1%

FLOORSMIN_AVG
Real number (ℝ)

Missing 

Distinct123
Distinct (%)1.9%
Missing13525
Missing (%)67.6%
Infinite0
Infinite (%)0.0%
Mean0.2345636448
Minimum0
Maximum1
Zeros133
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:05.787596image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0417
Q10.0833
median0.2083
Q30.375
95-th percentile0.5
Maximum1
Range1
Interquartile range (IQR)0.2917

Descriptive statistics

Standard deviation0.1619090753
Coefficient of variation (CV)0.690256478
Kurtosis1.256563107
Mean0.2345636448
Median Absolute Deviation (MAD)0.125
Skewness0.9431172683
Sum1518.7996
Variance0.02621454867
MonotonicityNot monotonic
2025-09-14T08:09:05.891595image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.2083 2152
 
10.8%
0.375 1149
 
5.7%
0.0417 1148
 
5.7%
0.0833 339
 
1.7%
0.4167 274
 
1.4%
0.1667 239
 
1.2%
0.125 197
 
1.0%
0 133
 
0.7%
0.5 124
 
0.6%
0.6667 78
 
0.4%
Other values (113) 642
 
3.2%
(Missing) 13525
67.6%
ValueCountFrequency (%)
0 133
0.7%
0.0158 1
 
< 0.1%
0.0208 3
 
< 0.1%
0.025 1
 
< 0.1%
0.0275 1
 
< 0.1%
ValueCountFrequency (%)
1 7
< 0.1%
0.9583 1
 
< 0.1%
0.9408 1
 
< 0.1%
0.9167 7
< 0.1%
0.875 2
 
< 0.1%

LANDAREA_AVG
Real number (ℝ)

Missing  Zeros 

Distinct1921
Distinct (%)23.4%
Missing11801
Missing (%)59.0%
Infinite0
Infinite (%)0.0%
Mean0.06559914624
Minimum0
Maximum1
Zeros1032
Zeros (%)5.2%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:05.996031image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.0182
median0.0479
Q30.0856
95-th percentile0.1893
Maximum1
Range1
Interquartile range (IQR)0.0674

Descriptive statistics

Standard deviation0.07947956221
Coefficient of variation (CV)1.211594461
Kurtosis35.1316238
Mean0.06559914624
Median Absolute Deviation (MAD)0.0324
Skewness4.414502768
Sum537.8474
Variance0.006317000809
MonotonicityNot monotonic
2025-09-14T08:09:06.090204image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1032
 
5.2%
0.0174 21
 
0.1%
0.0237 19
 
0.1%
0.0208 17
 
0.1%
0.0473 17
 
0.1%
0.0316 16
 
0.1%
0.0145 16
 
0.1%
0.0142 15
 
0.1%
0.0286 15
 
0.1%
0.0185 15
 
0.1%
Other values (1911) 7016
35.1%
(Missing) 11801
59.0%
ValueCountFrequency (%)
0 1032
5.2%
0.0001 1
 
< 0.1%
0.0002 1
 
< 0.1%
0.0004 1
 
< 0.1%
0.0006 1
 
< 0.1%
ValueCountFrequency (%)
1 10
0.1%
0.8947 1
 
< 0.1%
0.783 1
 
< 0.1%
0.7573 1
 
< 0.1%
0.7533 1
 
< 0.1%

LIVINGAPARTMENTS_AVG
Real number (ℝ)

Missing 

Distinct788
Distinct (%)12.3%
Missing13615
Missing (%)68.1%
Infinite0
Infinite (%)0.0%
Mean0.1008845106
Minimum0
Maximum1
Zeros20
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:06.186013image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0101
Q10.0504
median0.0756
Q30.121
95-th percentile0.274
Maximum1
Range1
Interquartile range (IQR)0.0706

Descriptive statistics

Standard deviation0.09116511345
Coefficient of variation (CV)0.9036581823
Kurtosis13.75534482
Mean0.1008845106
Median Absolute Deviation (MAD)0.0314
Skewness2.828973254
Sum644.1476
Variance0.00831107791
MonotonicityNot monotonic
2025-09-14T08:09:06.281520image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0672 284
 
1.4%
0.0504 265
 
1.3%
0.0588 168
 
0.8%
0.0756 164
 
0.8%
0.0841 117
 
0.6%
0.1009 108
 
0.5%
0.0605 105
 
0.5%
0.0067 102
 
0.5%
0.121 95
 
0.5%
0.0538 93
 
0.5%
Other values (778) 4884
 
24.4%
(Missing) 13615
68.1%
ValueCountFrequency (%)
0 20
0.1%
0.0008 4
 
< 0.1%
0.0017 15
0.1%
0.0025 7
 
< 0.1%
0.0034 30
0.1%
ValueCountFrequency (%)
1 4
< 0.1%
0.949 1
 
< 0.1%
0.8388 1
 
< 0.1%
0.78 1
 
< 0.1%
0.7296 1
 
< 0.1%

LIVINGAREA_AVG
Real number (ℝ)

Missing 

Distinct2796
Distinct (%)27.9%
Missing9977
Missing (%)49.9%
Infinite0
Infinite (%)0.0%
Mean0.1075006385
Minimum0
Maximum1
Zeros15
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:06.378709image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0081
Q10.0457
median0.0751
Q30.129
95-th percentile0.31989
Maximum1
Range1
Interquartile range (IQR)0.0833

Descriptive statistics

Standard deviation0.1102171108
Coefficient of variation (CV)1.025269359
Kurtosis11.83939555
Mean0.1075006385
Median Absolute Deviation (MAD)0.0389
Skewness2.810816541
Sum1077.4789
Variance0.01214781151
MonotonicityNot monotonic
2025-09-14T08:09:06.483020image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0696 21
 
0.1%
0.0639 19
 
0.1%
0.0644 17
 
0.1%
0.0497 16
 
0.1%
0.0608 16
 
0.1%
0.07 16
 
0.1%
0.0146 16
 
0.1%
0.0706 16
 
0.1%
0.0646 16
 
0.1%
0.0513 16
 
0.1%
Other values (2786) 9854
49.3%
(Missing) 9977
49.9%
ValueCountFrequency (%)
0 15
0.1%
0.0005 1
 
< 0.1%
0.0006 4
 
< 0.1%
0.0007 1
 
< 0.1%
0.0008 1
 
< 0.1%
ValueCountFrequency (%)
1 10
0.1%
0.9756 1
 
< 0.1%
0.8941 1
 
< 0.1%
0.8888 1
 
< 0.1%
0.8653 1
 
< 0.1%

NONLIVINGAPARTMENTS_AVG
Real number (ℝ)

Missing  Zeros 

Distinct134
Distinct (%)2.2%
Missing13818
Missing (%)69.1%
Infinite0
Infinite (%)0.0%
Mean0.008375153672
Minimum0
Maximum1
Zeros3608
Zeros (%)18.0%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:06.583547image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.0051
95-th percentile0.029
Maximum1
Range1
Interquartile range (IQR)0.0051

Descriptive statistics

Standard deviation0.04454717301
Coefficient of variation (CV)5.318967837
Kurtosis305.2872476
Mean0.008375153672
Median Absolute Deviation (MAD)0
Skewness16.00526183
Sum51.7752
Variance0.001984450623
MonotonicityNot monotonic
2025-09-14T08:09:06.687988image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3608
 
18.0%
0.0039 872
 
4.4%
0.0077 426
 
2.1%
0.0116 247
 
1.2%
0.0154 151
 
0.8%
0.0193 129
 
0.6%
0.0232 79
 
0.4%
0.027 72
 
0.4%
0.0019 71
 
0.4%
0.0309 59
 
0.3%
Other values (124) 468
 
2.3%
(Missing) 13818
69.1%
ValueCountFrequency (%)
0 3608
18.0%
0.0006 2
 
< 0.1%
0.0008 7
 
< 0.1%
0.0009 1
 
< 0.1%
0.001 7
 
< 0.1%
ValueCountFrequency (%)
1 4
< 0.1%
0.973 1
 
< 0.1%
0.9344 1
 
< 0.1%
0.9266 1
 
< 0.1%
0.7722 1
 
< 0.1%

NONLIVINGAREA_AVG
Real number (ℝ)

Missing  Zeros 

Distinct1391
Distinct (%)15.4%
Missing10984
Missing (%)54.9%
Infinite0
Infinite (%)0.0%
Mean0.02809932343
Minimum0
Maximum1
Zeros3864
Zeros (%)19.3%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:06.783385image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.0036
Q30.0282
95-th percentile0.12255
Maximum1
Range1
Interquartile range (IQR)0.0282

Descriptive statistics

Standard deviation0.06931549152
Coefficient of variation (CV)2.466802865
Kurtosis69.94210149
Mean0.02809932343
Median Absolute Deviation (MAD)0.0036
Skewness6.844946428
Sum253.3435
Variance0.004804637365
MonotonicityNot monotonic
2025-09-14T08:09:07.022733image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3864
 
19.3%
0.0036 40
 
0.2%
0.0046 38
 
0.2%
0.0012 33
 
0.2%
0.0044 31
 
0.2%
0.0011 31
 
0.2%
0.0023 28
 
0.1%
0.004 28
 
0.1%
0.0022 28
 
0.1%
0.0039 27
 
0.1%
Other values (1381) 4868
24.3%
(Missing) 10984
54.9%
ValueCountFrequency (%)
0 3864
19.3%
0.0001 12
 
0.1%
0.0002 9
 
< 0.1%
0.0003 7
 
< 0.1%
0.0004 13
 
0.1%
ValueCountFrequency (%)
1 8
< 0.1%
0.9591 1
 
< 0.1%
0.9558 2
 
< 0.1%
0.8651 1
 
< 0.1%
0.8572 1
 
< 0.1%

APARTMENTS_MODE
Real number (ℝ)

Missing 

Distinct528
Distinct (%)5.3%
Missing10097
Missing (%)50.5%
Infinite0
Infinite (%)0.0%
Mean0.1148990811
Minimum0
Maximum1
Zeros65
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:07.123411image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0084
Q10.0525
median0.084
Q30.1471
95-th percentile0.32329
Maximum1
Range1
Interquartile range (IQR)0.0946

Descriptive statistics

Standard deviation0.1082529187
Coefficient of variation (CV)0.9421565226
Kurtosis10.67230101
Mean0.1148990811
Median Absolute Deviation (MAD)0.0421
Skewness2.598243833
Sum1137.8456
Variance0.0117186944
MonotonicityNot monotonic
2025-09-14T08:09:07.222392image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.084 496
 
2.5%
0.063 467
 
2.3%
0.0735 290
 
1.5%
0.0945 287
 
1.4%
0.0084 257
 
1.3%
0.0756 226
 
1.1%
0.0168 219
 
1.1%
0.105 205
 
1.0%
0.0126 194
 
1.0%
0.1513 184
 
0.9%
Other values (518) 7078
35.4%
(Missing) 10097
50.5%
ValueCountFrequency (%)
0 65
0.3%
0.0011 22
 
0.1%
0.0021 67
0.3%
0.0032 27
 
0.1%
0.0042 87
0.4%
ValueCountFrequency (%)
1 8
< 0.1%
0.9842 1
 
< 0.1%
0.9149 1
 
< 0.1%
0.8992 1
 
< 0.1%
0.8792 1
 
< 0.1%

BASEMENTAREA_MODE
Real number (ℝ)

Missing  Zeros 

Distinct2115
Distinct (%)25.5%
Missing11714
Missing (%)58.6%
Infinite0
Infinite (%)0.0%
Mean0.08633211441
Minimum0
Maximum1
Zeros1106
Zeros (%)5.5%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:07.321754image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.040525
median0.0739
Q30.1119
95-th percentile0.221825
Maximum1
Range1
Interquartile range (IQR)0.071375

Descriptive statistics

Standard deviation0.0823884443
Coefficient of variation (CV)0.9543197785
Kurtosis25.49945091
Mean0.08633211441
Median Absolute Deviation (MAD)0.0354
Skewness3.489246486
Sum715.3479
Variance0.006787855754
MonotonicityNot monotonic
2025-09-14T08:09:07.419871image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1106
 
5.5%
0.1132 21
 
0.1%
0.0849 20
 
0.1%
0.083 19
 
0.1%
0.0826 19
 
0.1%
0.0875 19
 
0.1%
0.0792 17
 
0.1%
0.0877 16
 
0.1%
0.0642 16
 
0.1%
0.0858 16
 
0.1%
Other values (2105) 7017
35.1%
(Missing) 11714
58.6%
ValueCountFrequency (%)
0 1106
5.5%
0.0001 7
 
< 0.1%
0.0002 3
 
< 0.1%
0.0003 1
 
< 0.1%
0.0005 5
 
< 0.1%
ValueCountFrequency (%)
1 10
0.1%
0.8457 1
 
< 0.1%
0.8223 1
 
< 0.1%
0.8068 1
 
< 0.1%
0.7548 1
 
< 0.1%

YEARS_BEGINEXPLUATATION_MODE
Real number (ℝ)

Missing 

Distinct137
Distinct (%)1.3%
Missing9707
Missing (%)48.5%
Infinite0
Infinite (%)0.0%
Mean0.976468056
Minimum0
Maximum1
Zeros11
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:07.518205image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.9682
Q10.9762
median0.9816
Q30.9866
95-th percentile0.9955
Maximum1
Range1
Interquartile range (IQR)0.0104

Descriptive statistics

Standard deviation0.06766287775
Coefficient of variation (CV)0.06929348823
Kurtosis199.2387892
Mean0.976468056
Median Absolute Deviation (MAD)0.005
Skewness-14.04917715
Sum10050.7857
Variance0.004578265025
MonotonicityNot monotonic
2025-09-14T08:09:07.630940image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.9876 293
 
1.5%
0.9806 287
 
1.4%
0.9851 270
 
1.4%
0.9871 268
 
1.3%
0.9816 266
 
1.3%
0.9866 264
 
1.3%
0.9861 264
 
1.3%
0.9796 261
 
1.3%
0.9821 259
 
1.3%
0.9791 258
 
1.3%
Other values (127) 7603
38.0%
(Missing) 9707
48.5%
ValueCountFrequency (%)
0 11
 
0.1%
0.0005 36
0.2%
0.0184 1
 
< 0.1%
0.4518 1
 
< 0.1%
0.5943 1
 
< 0.1%
ValueCountFrequency (%)
1 12
 
0.1%
0.9995 46
0.2%
0.999 59
0.3%
0.9985 56
0.3%
0.998 64
0.3%

YEARS_BUILD_MODE
Real number (ℝ)

Missing 

Distinct120
Distinct (%)1.8%
Missing13202
Missing (%)66.0%
Infinite0
Infinite (%)0.0%
Mean0.7581805237
Minimum0
Maximum1
Zeros5
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:07.746152image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.6014
Q10.6929
median0.7648
Q30.8236
95-th percentile0.9543
Maximum1
Range1
Interquartile range (IQR)0.1307

Descriptive statistics

Standard deviation0.1121790938
Coefficient of variation (CV)0.14795829
Kurtosis4.516080581
Mean0.7581805237
Median Absolute Deviation (MAD)0.0653
Skewness-1.028294323
Sum5154.1112
Variance0.01258414908
MonotonicityNot monotonic
2025-09-14T08:09:07.848826image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.8367 215
 
1.1%
0.8171 192
 
1.0%
0.8236 191
 
1.0%
0.804 188
 
0.9%
0.8301 186
 
0.9%
0.8105 185
 
0.9%
0.7517 184
 
0.9%
0.7583 181
 
0.9%
0.7452 179
 
0.9%
0.7125 176
 
0.9%
Other values (110) 4921
 
24.6%
(Missing) 13202
66.0%
ValueCountFrequency (%)
0 5
< 0.1%
0.0265 1
 
< 0.1%
0.0395 1
 
< 0.1%
0.0461 1
 
< 0.1%
0.0722 1
 
< 0.1%
ValueCountFrequency (%)
1 11
 
0.1%
0.9935 33
0.2%
0.9869 45
0.2%
0.9804 44
0.2%
0.9739 50
0.2%

COMMONAREA_MODE
Real number (ℝ)

Missing  Zeros 

Distinct1383
Distinct (%)22.7%
Missing13918
Missing (%)69.6%
Infinite0
Infinite (%)0.0%
Mean0.04330746465
Minimum0
Maximum1
Zeros669
Zeros (%)3.3%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:07.951915image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.0071
median0.0189
Q30.0488
95-th percentile0.1596
Maximum1
Range1
Interquartile range (IQR)0.0417

Descriptive statistics

Standard deviation0.07992892092
Coefficient of variation (CV)1.845615336
Kurtosis48.56013851
Mean0.04330746465
Median Absolute Deviation (MAD)0.0163
Skewness5.774322599
Sum263.396
Variance0.006388632399
MonotonicityNot monotonic
2025-09-14T08:09:08.081944image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 669
 
3.3%
0.0079 35
 
0.2%
0.007 34
 
0.2%
0.0078 32
 
0.2%
0.008 28
 
0.1%
0.0095 27
 
0.1%
0.0072 26
 
0.1%
0.0097 26
 
0.1%
0.0082 24
 
0.1%
0.0088 24
 
0.1%
Other values (1373) 5157
 
25.8%
(Missing) 13918
69.6%
ValueCountFrequency (%)
0 669
3.3%
0.0001 4
 
< 0.1%
0.0002 1
 
< 0.1%
0.0003 2
 
< 0.1%
0.0004 4
 
< 0.1%
ValueCountFrequency (%)
1 7
< 0.1%
0.9591 1
 
< 0.1%
0.8936 1
 
< 0.1%
0.8889 1
 
< 0.1%
0.885 1
 
< 0.1%

ELEVATORS_MODE
Real number (ℝ)

Missing  Zeros 

Distinct26
Distinct (%)0.3%
Missing10601
Missing (%)53.0%
Infinite0
Infinite (%)0.0%
Mean0.07487805086
Minimum0
Maximum1
Zeros5834
Zeros (%)29.2%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:08.176548image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.1208
95-th percentile0.3222
Maximum1
Range1
Interquartile range (IQR)0.1208

Descriptive statistics

Standard deviation0.1327087756
Coefficient of variation (CV)1.772332133
Kurtosis8.825932779
Mean0.07487805086
Median Absolute Deviation (MAD)0
Skewness2.582290542
Sum703.7788
Variance0.01761161912
MonotonicityNot monotonic
2025-09-14T08:09:08.270846image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0 5834
29.2%
0.0806 774
 
3.9%
0.1611 616
 
3.1%
0.2417 413
 
2.1%
0.1208 402
 
2.0%
0.0403 305
 
1.5%
0.2014 286
 
1.4%
0.3222 189
 
0.9%
0.282 141
 
0.7%
0.3625 97
 
0.5%
Other values (16) 342
 
1.7%
(Missing) 10601
53.0%
ValueCountFrequency (%)
0 5834
29.2%
0.0403 305
 
1.5%
0.0806 774
 
3.9%
0.1208 402
 
2.0%
0.1611 616
 
3.1%
ValueCountFrequency (%)
1 7
< 0.1%
0.9667 8
< 0.1%
0.9264 1
 
< 0.1%
0.8862 7
< 0.1%
0.8459 3
 
< 0.1%

ENTRANCES_MODE
Real number (ℝ)

Missing 

Distinct29
Distinct (%)0.3%
Missing10048
Missing (%)50.2%
Infinite0
Infinite (%)0.0%
Mean0.1445028939
Minimum0
Maximum1
Zeros24
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:08.361179image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0345
Q10.069
median0.1379
Q30.2069
95-th percentile0.3103
Maximum1
Range1
Interquartile range (IQR)0.1379

Descriptive statistics

Standard deviation0.09996839106
Coefficient of variation (CV)0.6918089207
Kurtosis11.29289354
Mean0.1445028939
Median Absolute Deviation (MAD)0.0689
Skewness2.378060195
Sum1438.0928
Variance0.009993679212
MonotonicityNot monotonic
2025-09-14T08:09:08.477434image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
0.1379 2337
 
11.7%
0.069 1717
 
8.6%
0.1034 1370
 
6.9%
0.0345 1279
 
6.4%
0.2069 1270
 
6.3%
0.1724 618
 
3.1%
0.2759 503
 
2.5%
0.2414 271
 
1.4%
0.3103 138
 
0.7%
0.3448 120
 
0.6%
Other values (19) 329
 
1.6%
(Missing) 10048
50.2%
ValueCountFrequency (%)
0 24
 
0.1%
0.0345 1279
6.4%
0.069 1717
8.6%
0.1034 1370
6.9%
0.1379 2337
11.7%
ValueCountFrequency (%)
1 7
< 0.1%
0.9655 2
 
< 0.1%
0.931 1
 
< 0.1%
0.8966 7
< 0.1%
0.8276 3
< 0.1%

FLOORSMAX_MODE
Real number (ℝ)

Missing  Zeros 

Distinct25
Distinct (%)0.2%
Missing9913
Missing (%)49.6%
Infinite0
Infinite (%)0.0%
Mean0.2234272033
Minimum0
Maximum1
Zeros250
Zeros (%)1.2%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:08.576946image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0417
Q10.1667
median0.1667
Q30.3333
95-th percentile0.4583
Maximum1
Range1
Interquartile range (IQR)0.1666

Descriptive statistics

Standard deviation0.1455335169
Coefficient of variation (CV)0.6513688339
Kurtosis2.523126835
Mean0.2234272033
Median Absolute Deviation (MAD)0.0834
Skewness1.250382502
Sum2253.7102
Variance0.02118000454
MonotonicityNot monotonic
2025-09-14T08:09:08.675421image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
0.1667 4240
21.2%
0.3333 2253
 
11.3%
0.0417 1010
 
5.1%
0.375 533
 
2.7%
0.125 492
 
2.5%
0.0833 409
 
2.0%
0 250
 
1.2%
0.4583 213
 
1.1%
0.5417 138
 
0.7%
0.6667 130
 
0.7%
Other values (15) 419
 
2.1%
(Missing) 9913
49.6%
ValueCountFrequency (%)
0 250
 
1.2%
0.0417 1010
 
5.1%
0.0833 409
 
2.0%
0.125 492
 
2.5%
0.1667 4240
21.2%
ValueCountFrequency (%)
1 11
0.1%
0.9583 4
 
< 0.1%
0.9167 3
 
< 0.1%
0.875 19
0.1%
0.8333 2
 
< 0.1%

FLOORSMIN_MODE
Real number (ℝ)

Missing 

Distinct25
Distinct (%)0.4%
Missing13525
Missing (%)67.6%
Infinite0
Infinite (%)0.0%
Mean0.2307094981
Minimum0
Maximum1
Zeros146
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:08.768651image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0417
Q10.0833
median0.2083
Q30.375
95-th percentile0.5
Maximum1
Range1
Interquartile range (IQR)0.2917

Descriptive statistics

Standard deviation0.1617921201
Coefficient of variation (CV)0.7012807078
Kurtosis1.220685824
Mean0.2307094981
Median Absolute Deviation (MAD)0.1666
Skewness0.949158348
Sum1493.844
Variance0.02617669013
MonotonicityNot monotonic
2025-09-14T08:09:08.868548image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
0.2083 2270
 
11.3%
0.375 1221
 
6.1%
0.0417 1216
 
6.1%
0.0833 361
 
1.8%
0.4167 284
 
1.4%
0.1667 253
 
1.3%
0.125 183
 
0.9%
0 146
 
0.7%
0.5 138
 
0.7%
0.7083 82
 
0.4%
Other values (15) 321
 
1.6%
(Missing) 13525
67.6%
ValueCountFrequency (%)
0 146
 
0.7%
0.0417 1216
6.1%
0.0833 361
 
1.8%
0.125 183
 
0.9%
0.1667 253
 
1.3%
ValueCountFrequency (%)
1 6
< 0.1%
0.9583 2
 
< 0.1%
0.9167 7
< 0.1%
0.875 2
 
< 0.1%
0.8333 4
< 0.1%

LANDAREA_MODE
Real number (ℝ)

Missing  Zeros 

Distinct1903
Distinct (%)23.2%
Missing11801
Missing (%)59.0%
Infinite0
Infinite (%)0.0%
Mean0.06436125137
Minimum0
Maximum1
Zeros1158
Zeros (%)5.8%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:09.007148image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.016
median0.0451
Q30.0844
95-th percentile0.1913
Maximum1
Range1
Interquartile range (IQR)0.0684

Descriptive statistics

Standard deviation0.08067072479
Coefficient of variation (CV)1.253405163
Kurtosis33.23552723
Mean0.06436125137
Median Absolute Deviation (MAD)0.0322
Skewness4.339217478
Sum527.6979
Variance0.006507765838
MonotonicityNot monotonic
2025-09-14T08:09:09.142192image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1158
 
5.8%
0.0484 19
 
0.1%
0.0242 18
 
0.1%
0.0152 18
 
0.1%
0.0149 18
 
0.1%
0.0189 18
 
0.1%
0.0111 17
 
0.1%
0.0181 17
 
0.1%
0.0213 16
 
0.1%
0.0299 16
 
0.1%
Other values (1893) 6884
34.4%
(Missing) 11801
59.0%
ValueCountFrequency (%)
0 1158
5.8%
0.0001 2
 
< 0.1%
0.0002 1
 
< 0.1%
0.0004 1
 
< 0.1%
0.0006 1
 
< 0.1%
ValueCountFrequency (%)
1 9
< 0.1%
0.9152 1
 
< 0.1%
0.8008 1
 
< 0.1%
0.7745 1
 
< 0.1%
0.7705 1
 
< 0.1%

LIVINGAPARTMENTS_MODE
Real number (ℝ)

Missing 

Distinct490
Distinct (%)7.7%
Missing13615
Missing (%)68.1%
Infinite0
Infinite (%)0.0%
Mean0.1060528583
Minimum0
Maximum1
Zeros27
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:09.247458image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.011
Q10.0551
median0.0771
Q30.1313
95-th percentile0.2966
Maximum1
Range1
Interquartile range (IQR)0.0762

Descriptive statistics

Standard deviation0.09737270753
Coefficient of variation (CV)0.9181525998
Kurtosis12.11752441
Mean0.1060528583
Median Absolute Deviation (MAD)0.0331
Skewness2.748874658
Sum677.1475
Variance0.009481444171
MonotonicityNot monotonic
2025-09-14T08:09:09.495411image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0735 333
 
1.7%
0.0551 314
 
1.6%
0.0643 187
 
0.9%
0.0826 176
 
0.9%
0.0661 134
 
0.7%
0.0918 129
 
0.6%
0.0073 116
 
0.6%
0.1102 109
 
0.5%
0.0588 103
 
0.5%
0.0992 101
 
0.5%
Other values (480) 4683
 
23.4%
(Missing) 13615
68.1%
ValueCountFrequency (%)
0 27
0.1%
0.0009 6
 
< 0.1%
0.0018 16
0.1%
0.0028 9
 
< 0.1%
0.0037 34
0.2%
ValueCountFrequency (%)
1 4
< 0.1%
0.9164 1
 
< 0.1%
0.8522 1
 
< 0.1%
0.7971 1
 
< 0.1%
0.7521 1
 
< 0.1%

LIVINGAREA_MODE
Real number (ℝ)

Missing 

Distinct2780
Distinct (%)27.7%
Missing9977
Missing (%)49.9%
Infinite0
Infinite (%)0.0%
Mean0.1060021151
Minimum0
Maximum1
Zeros25
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:09.593213image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0075
Q10.0422
median0.0732
Q30.1246
95-th percentile0.32101
Maximum1
Range1
Interquartile range (IQR)0.0824

Descriptive statistics

Standard deviation0.1124167843
Coefficient of variation (CV)1.06051454
Kurtosis12.43816039
Mean0.1060021151
Median Absolute Deviation (MAD)0.0398
Skewness2.91058581
Sum1062.4592
Variance0.0126375334
MonotonicityNot monotonic
2025-09-14T08:09:09.696993image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 25
 
0.1%
0.0726 23
 
0.1%
0.0532 19
 
0.1%
0.0556 18
 
0.1%
0.0666 18
 
0.1%
0.0538 18
 
0.1%
0.073 17
 
0.1%
0.0529 17
 
0.1%
0.0528 17
 
0.1%
0.0673 17
 
0.1%
Other values (2770) 9834
49.2%
(Missing) 9977
49.9%
ValueCountFrequency (%)
0 25
0.1%
0.0005 2
 
< 0.1%
0.0006 2
 
< 0.1%
0.0007 4
 
< 0.1%
0.0008 2
 
< 0.1%
ValueCountFrequency (%)
1 11
0.1%
0.9315 1
 
< 0.1%
0.926 1
 
< 0.1%
0.9015 1
 
< 0.1%
0.8957 1
 
< 0.1%

NONLIVINGAPARTMENTS_MODE
Real number (ℝ)

Missing  Zeros 

Distinct67
Distinct (%)1.1%
Missing13818
Missing (%)69.1%
Infinite0
Infinite (%)0.0%
Mean0.007827078615
Minimum0
Maximum1
Zeros3903
Zeros (%)19.5%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:09.802057image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.0039
95-th percentile0.0272
Maximum1
Range1
Interquartile range (IQR)0.0039

Descriptive statistics

Standard deviation0.04427974032
Coefficient of variation (CV)5.657249978
Kurtosis317.6928974
Mean0.007827078615
Median Absolute Deviation (MAD)0
Skewness16.42026612
Sum48.387
Variance0.001960695403
MonotonicityNot monotonic
2025-09-14T08:09:09.900293image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3903
 
19.5%
0.0039 882
 
4.4%
0.0078 444
 
2.2%
0.0117 247
 
1.2%
0.0156 153
 
0.8%
0.0195 125
 
0.6%
0.0233 74
 
0.4%
0.0272 66
 
0.3%
0.0311 62
 
0.3%
0.035 38
 
0.2%
Other values (57) 188
 
0.9%
(Missing) 13818
69.1%
ValueCountFrequency (%)
0 3903
19.5%
0.0039 882
 
4.4%
0.0078 444
 
2.2%
0.0117 247
 
1.2%
0.0156 153
 
0.8%
ValueCountFrequency (%)
1 4
< 0.1%
0.9805 1
 
< 0.1%
0.9416 1
 
< 0.1%
0.9339 1
 
< 0.1%
0.7782 1
 
< 0.1%

NONLIVINGAREA_MODE
Real number (ℝ)

Missing  Zeros 

Distinct1372
Distinct (%)15.2%
Missing10984
Missing (%)54.9%
Infinite0
Infinite (%)0.0%
Mean0.0266484472
Minimum0
Maximum1
Zeros4419
Zeros (%)22.1%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:10.008492image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.00105
Q30.0234
95-th percentile0.12485
Maximum1
Range1
Interquartile range (IQR)0.0234

Descriptive statistics

Standard deviation0.07049296696
Coefficient of variation (CV)2.645293605
Kurtosis72.55318305
Mean0.0266484472
Median Absolute Deviation (MAD)0.00105
Skewness7.019927161
Sum240.2624
Variance0.004969258391
MonotonicityNot monotonic
2025-09-14T08:09:10.120247image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 4419
22.1%
0.0011 38
 
0.2%
0.0012 35
 
0.2%
0.0049 32
 
0.2%
0.0033 30
 
0.1%
0.0055 30
 
0.1%
0.0046 28
 
0.1%
0.003 27
 
0.1%
0.0045 27
 
0.1%
0.0038 27
 
0.1%
Other values (1362) 4323
 
21.6%
(Missing) 10984
54.9%
ValueCountFrequency (%)
0 4419
22.1%
0.0001 8
 
< 0.1%
0.0002 10
 
0.1%
0.0003 3
 
< 0.1%
0.0004 8
 
< 0.1%
ValueCountFrequency (%)
1 11
0.1%
0.9159 1
 
< 0.1%
0.9075 1
 
< 0.1%
0.9057 1
 
< 0.1%
0.8619 1
 
< 0.1%

APARTMENTS_MEDI
Real number (ℝ)

Missing 

Distinct719
Distinct (%)7.3%
Missing10097
Missing (%)50.5%
Infinite0
Infinite (%)0.0%
Mean0.118427315
Minimum0
Maximum1
Zeros44
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:10.223622image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0083
Q10.0583
median0.0874
Q30.1499
95-th percentile0.3321
Maximum1
Range1
Interquartile range (IQR)0.0916

Descriptive statistics

Standard deviation0.108757712
Coefficient of variation (CV)0.9183498925
Kurtosis10.09717026
Mean0.118427315
Median Absolute Deviation (MAD)0.0438
Skewness2.525127355
Sum1172.7857
Variance0.01182823991
MonotonicityNot monotonic
2025-09-14T08:09:10.339822image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0833 464
 
2.3%
0.0625 422
 
2.1%
0.0937 279
 
1.4%
0.0729 279
 
1.4%
0.0083 224
 
1.1%
0.1041 203
 
1.0%
0.0167 203
 
1.0%
0.0749 199
 
1.0%
0.0125 184
 
0.9%
0.1499 180
 
0.9%
Other values (709) 7266
36.3%
(Missing) 10097
50.5%
ValueCountFrequency (%)
0 44
0.2%
0.001 13
 
0.1%
0.0016 1
 
< 0.1%
0.0021 56
0.3%
0.0031 25
0.1%
ValueCountFrequency (%)
1 7
< 0.1%
0.991 1
 
< 0.1%
0.9753 1
 
< 0.1%
0.9066 1
 
< 0.1%
0.891 1
 
< 0.1%

BASEMENTAREA_MEDI
Real number (ℝ)

Missing  Zeros 

Distinct2104
Distinct (%)25.4%
Missing11714
Missing (%)58.6%
Infinite0
Infinite (%)0.0%
Mean0.08684750181
Minimum0
Maximum1
Zeros984
Zeros (%)4.9%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:10.453892image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.0436
median0.076
Q30.1111
95-th percentile0.2167
Maximum1
Range1
Interquartile range (IQR)0.0675

Descriptive statistics

Standard deviation0.07982719129
Coefficient of variation (CV)0.9191650839
Kurtosis27.18389532
Mean0.08684750181
Median Absolute Deviation (MAD)0.0339
Skewness3.556853573
Sum719.6184
Variance0.006372380469
MonotonicityNot monotonic
2025-09-14T08:09:10.565141image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 984
 
4.9%
0.0818 23
 
0.1%
0.0625 21
 
0.1%
0.08 21
 
0.1%
0.0803 20
 
0.1%
0.0796 20
 
0.1%
0.1091 20
 
0.1%
0.0804 19
 
0.1%
0.0636 18
 
0.1%
0.0655 18
 
0.1%
Other values (2094) 7122
35.6%
(Missing) 11714
58.6%
ValueCountFrequency (%)
0 984
4.9%
0.0001 4
 
< 0.1%
0.0002 5
 
< 0.1%
0.0005 7
 
< 0.1%
0.0006 3
 
< 0.1%
ValueCountFrequency (%)
1 9
< 0.1%
0.9677 1
 
< 0.1%
0.815 1
 
< 0.1%
0.7924 1
 
< 0.1%
0.7775 1
 
< 0.1%

YEARS_BEGINEXPLUATATION_MEDI
Real number (ℝ)

Missing 

Distinct136
Distinct (%)1.3%
Missing9707
Missing (%)48.5%
Infinite0
Infinite (%)0.0%
Mean0.9773537355
Minimum0
Maximum1
Zeros39
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:10.667669image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.9687
Q10.9767
median0.9816
Q30.9866
95-th percentile0.996
Maximum1
Range1
Interquartile range (IQR)0.0099

Descriptive statistics

Standard deviation0.06249586181
Coefficient of variation (CV)0.06394395349
Kurtosis230.7456235
Mean0.9773537355
Median Absolute Deviation (MAD)0.005
Skewness-15.05146747
Sum10059.902
Variance0.003905732743
MonotonicityNot monotonic
2025-09-14T08:09:10.782058image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.9876 294
 
1.5%
0.9871 283
 
1.4%
0.9806 280
 
1.4%
0.9861 269
 
1.3%
0.9851 269
 
1.3%
0.9821 267
 
1.3%
0.9831 266
 
1.3%
0.9811 266
 
1.3%
0.9816 265
 
1.3%
0.9856 264
 
1.3%
Other values (126) 7570
37.9%
(Missing) 9707
48.5%
ValueCountFrequency (%)
0 39
0.2%
0.0179 1
 
< 0.1%
0.4883 1
 
< 0.1%
0.4898 1
 
< 0.1%
0.4903 1
 
< 0.1%
ValueCountFrequency (%)
1 13
 
0.1%
0.9995 47
0.2%
0.999 59
0.3%
0.9985 57
0.3%
0.998 70
0.4%

YEARS_BUILD_MEDI
Real number (ℝ)

Missing 

Distinct118
Distinct (%)1.7%
Missing13202
Missing (%)66.0%
Infinite0
Infinite (%)0.0%
Mean0.7546869668
Minimum0
Maximum1
Zeros3
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:10.894687image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.5975
Q10.6914
median0.7585
Q30.8256
95-th percentile0.953
Maximum1
Range1
Interquartile range (IQR)0.1342

Descriptive statistics

Standard deviation0.1137480691
Coefficient of variation (CV)0.1507221856
Kurtosis3.997488215
Mean0.7546869668
Median Absolute Deviation (MAD)0.0671
Skewness-0.9561776422
Sum5130.362
Variance0.01293862322
MonotonicityNot monotonic
2025-09-14T08:09:11.005926image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.8323 211
 
1.1%
0.8256 197
 
1.0%
0.8054 192
 
1.0%
0.8121 190
 
0.9%
0.7451 189
 
0.9%
0.7987 189
 
0.9%
0.8189 183
 
0.9%
0.7518 182
 
0.9%
0.7383 176
 
0.9%
0.7316 175
 
0.9%
Other values (108) 4914
 
24.6%
(Missing) 13202
66.0%
ValueCountFrequency (%)
0 3
< 0.1%
0.0138 1
 
< 0.1%
0.0205 1
 
< 0.1%
0.0473 1
 
< 0.1%
0.0674 2
< 0.1%
ValueCountFrequency (%)
1 12
 
0.1%
0.9933 33
0.2%
0.9866 45
0.2%
0.9799 44
0.2%
0.9732 51
0.3%

COMMONAREA_MEDI
Real number (ℝ)

Missing  Zeros 

Distinct1404
Distinct (%)23.1%
Missing13918
Missing (%)69.6%
Infinite0
Infinite (%)0.0%
Mean0.04546349885
Minimum0
Maximum1
Zeros604
Zeros (%)3.0%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:11.111121image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.0076
median0.0207
Q30.050675
95-th percentile0.167895
Maximum1
Range1
Interquartile range (IQR)0.043075

Descriptive statistics

Standard deviation0.08219770175
Coefficient of variation (CV)1.80799331
Kurtosis44.61193563
Mean0.04546349885
Median Absolute Deviation (MAD)0.017
Skewness5.565022861
Sum276.509
Variance0.006756462173
MonotonicityNot monotonic
2025-09-14T08:09:11.227549image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 604
 
3.0%
0.008 33
 
0.2%
0.0079 32
 
0.2%
0.0078 28
 
0.1%
0.007 26
 
0.1%
0.0097 26
 
0.1%
0.001 25
 
0.1%
0.0095 25
 
0.1%
0.0069 23
 
0.1%
0.0088 22
 
0.1%
Other values (1394) 5238
 
26.2%
(Missing) 13918
69.6%
ValueCountFrequency (%)
0 604
3.0%
0.0001 3
 
< 0.1%
0.0002 1
 
< 0.1%
0.0003 4
 
< 0.1%
0.0004 3
 
< 0.1%
ValueCountFrequency (%)
1 7
< 0.1%
0.9565 1
 
< 0.1%
0.8911 1
 
< 0.1%
0.8864 1
 
< 0.1%
0.8825 1
 
< 0.1%

ELEVATORS_MEDI
Real number (ℝ)

Missing  Zeros 

Distinct41
Distinct (%)0.4%
Missing10601
Missing (%)53.0%
Infinite0
Infinite (%)0.0%
Mean0.07858282796
Minimum0
Maximum1
Zeros5651
Zeros (%)28.3%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:11.321076image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.12
95-th percentile0.36
Maximum1
Range1
Interquartile range (IQR)0.12

Descriptive statistics

Standard deviation0.1345778845
Coefficient of variation (CV)1.712560975
Kurtosis8.049500951
Mean0.07858282796
Median Absolute Deviation (MAD)0
Skewness2.471622299
Sum738.6
Variance0.01811120699
MonotonicityNot monotonic
2025-09-14T08:09:11.419963image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
0 5651
28.3%
0.08 731
 
3.7%
0.16 591
 
3.0%
0.24 422
 
2.1%
0.12 418
 
2.1%
0.04 302
 
1.5%
0.2 289
 
1.4%
0.32 195
 
1.0%
0.28 145
 
0.7%
0.36 103
 
0.5%
Other values (31) 552
 
2.8%
(Missing) 10601
53.0%
ValueCountFrequency (%)
0 5651
28.3%
0.02 25
 
0.1%
0.04 302
 
1.5%
0.06 33
 
0.2%
0.08 731
 
3.7%
ValueCountFrequency (%)
1 7
< 0.1%
0.96 8
< 0.1%
0.92 1
 
< 0.1%
0.88 7
< 0.1%
0.84 3
 
< 0.1%

ENTRANCES_MEDI
Real number (ℝ)

Missing 

Distinct43
Distinct (%)0.4%
Missing10048
Missing (%)50.2%
Infinite0
Infinite (%)0.0%
Mean0.1487346463
Minimum0
Maximum1
Zeros21
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:11.521632image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0345
Q10.069
median0.1379
Q30.2069
95-th percentile0.3103
Maximum1
Range1
Interquartile range (IQR)0.1379

Descriptive statistics

Standard deviation0.09984519496
Coefficient of variation (CV)0.6712974915
Kurtosis11.59287068
Mean0.1487346463
Median Absolute Deviation (MAD)0.0689
Skewness2.401819175
Sum1480.2072
Variance0.009969062956
MonotonicityNot monotonic
2025-09-14T08:09:11.766407image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
0.1379 2293
 
11.5%
0.069 1534
 
7.7%
0.1034 1360
 
6.8%
0.2069 1284
 
6.4%
0.0345 1070
 
5.3%
0.1724 657
 
3.3%
0.2759 501
 
2.5%
0.2414 293
 
1.5%
0.3103 141
 
0.7%
0.3448 121
 
0.6%
Other values (33) 698
 
3.5%
(Missing) 10048
50.2%
ValueCountFrequency (%)
0 21
 
0.1%
0.0345 1070
5.3%
0.0517 45
 
0.2%
0.069 1534
7.7%
0.0862 91
 
0.5%
ValueCountFrequency (%)
1 8
< 0.1%
0.9655 2
 
< 0.1%
0.931 1
 
< 0.1%
0.8966 7
< 0.1%
0.8276 3
 
< 0.1%

FLOORSMAX_MEDI
Real number (ℝ)

Missing  Zeros 

Distinct43
Distinct (%)0.4%
Missing9913
Missing (%)49.6%
Infinite0
Infinite (%)0.0%
Mean0.2270618321
Minimum0
Maximum1
Zeros223
Zeros (%)1.1%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:11.862151image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0417
Q10.1667
median0.1667
Q30.3333
95-th percentile0.5
Maximum1
Range1
Interquartile range (IQR)0.1666

Descriptive statistics

Standard deviation0.1465007275
Coefficient of variation (CV)0.6452019089
Kurtosis2.48127971
Mean0.2270618321
Median Absolute Deviation (MAD)0.0834
Skewness1.246161191
Sum2290.3727
Variance0.02146246315
MonotonicityNot monotonic
2025-09-14T08:09:11.958050image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
0.1667 4099
20.5%
0.3333 2194
 
11.0%
0.0417 949
 
4.7%
0.375 526
 
2.6%
0.125 470
 
2.4%
0.0833 399
 
2.0%
0 223
 
1.1%
0.4583 209
 
1.0%
0.25 140
 
0.7%
0.5417 140
 
0.7%
Other values (33) 738
 
3.7%
(Missing) 9913
49.6%
ValueCountFrequency (%)
0 223
 
1.1%
0.0208 7
 
< 0.1%
0.0417 949
4.7%
0.0625 10
 
0.1%
0.0833 399
2.0%
ValueCountFrequency (%)
1 11
0.1%
0.9583 4
 
< 0.1%
0.9167 3
 
< 0.1%
0.875 19
0.1%
0.8333 3
 
< 0.1%

FLOORSMIN_MEDI
Real number (ℝ)

Missing 

Distinct44
Distinct (%)0.7%
Missing13525
Missing (%)67.6%
Infinite0
Infinite (%)0.0%
Mean0.234467861
Minimum0
Maximum1
Zeros135
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:12.052153image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0417
Q10.0833
median0.2083
Q30.375
95-th percentile0.5
Maximum1
Range1
Interquartile range (IQR)0.2917

Descriptive statistics

Standard deviation0.162698243
Coefficient of variation (CV)0.6939042403
Kurtosis1.247848419
Mean0.234467861
Median Absolute Deviation (MAD)0.1666
Skewness0.9483302998
Sum1518.1794
Variance0.02647071827
MonotonicityNot monotonic
2025-09-14T08:09:12.148260image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
0.2083 2208
 
11.0%
0.375 1191
 
6.0%
0.0417 1169
 
5.8%
0.0833 339
 
1.7%
0.4167 282
 
1.4%
0.1667 243
 
1.2%
0.125 199
 
1.0%
0.5 137
 
0.7%
0 135
 
0.7%
0.6667 80
 
0.4%
Other values (34) 492
 
2.5%
(Missing) 13525
67.6%
ValueCountFrequency (%)
0 135
 
0.7%
0.0208 3
 
< 0.1%
0.0417 1169
5.8%
0.0625 1
 
< 0.1%
0.0833 339
 
1.7%
ValueCountFrequency (%)
1 7
< 0.1%
0.9583 2
 
< 0.1%
0.9167 7
< 0.1%
0.875 2
 
< 0.1%
0.8542 1
 
< 0.1%

LANDAREA_MEDI
Real number (ℝ)

Missing  Zeros 

Distinct1944
Distinct (%)23.7%
Missing11801
Missing (%)59.0%
Infinite0
Infinite (%)0.0%
Mean0.06650492743
Minimum0
Maximum1
Zeros1056
Zeros (%)5.3%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:12.243881image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.0182
median0.0484
Q30.0868
95-th percentile0.19224
Maximum1
Range1
Interquartile range (IQR)0.0686

Descriptive statistics

Standard deviation0.08093033841
Coefficient of variation (CV)1.216907401
Kurtosis34.00667256
Mean0.06650492743
Median Absolute Deviation (MAD)0.033
Skewness4.37212554
Sum545.2739
Variance0.006549719676
MonotonicityNot monotonic
2025-09-14T08:09:12.344360image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1056
 
5.3%
0.0177 20
 
0.1%
0.0148 18
 
0.1%
0.0188 17
 
0.1%
0.0321 16
 
0.1%
0.0241 16
 
0.1%
0.0482 16
 
0.1%
0.0551 15
 
0.1%
0.0139 15
 
0.1%
0.0291 15
 
0.1%
Other values (1934) 6995
35.0%
(Missing) 11801
59.0%
ValueCountFrequency (%)
0 1056
5.3%
0.0001 1
 
< 0.1%
0.0002 1
 
< 0.1%
0.0005 1
 
< 0.1%
0.0006 1
 
< 0.1%
ValueCountFrequency (%)
1 10
0.1%
0.9103 1
 
< 0.1%
0.7966 1
 
< 0.1%
0.7704 1
 
< 0.1%
0.7664 1
 
< 0.1%

LIVINGAPARTMENTS_MEDI
Real number (ℝ)

Missing 

Distinct629
Distinct (%)9.9%
Missing13615
Missing (%)68.1%
Infinite0
Infinite (%)0.0%
Mean0.1022246515
Minimum0
Maximum1
Zeros20
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:12.440959image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0103
Q10.0513
median0.0761
Q30.1231
95-th percentile0.2788
Maximum1
Range1
Interquartile range (IQR)0.0718

Descriptive statistics

Standard deviation0.09265193603
Coefficient of variation (CV)0.9063560956
Kurtosis13.43471212
Mean0.1022246515
Median Absolute Deviation (MAD)0.0316
Skewness2.815474538
Sum652.7044
Variance0.00858438125
MonotonicityNot monotonic
2025-09-14T08:09:12.537143image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0684 308
 
1.5%
0.0513 283
 
1.4%
0.077 175
 
0.9%
0.0599 173
 
0.9%
0.0855 125
 
0.6%
0.0616 122
 
0.6%
0.1026 110
 
0.5%
0.1231 102
 
0.5%
0.0068 102
 
0.5%
0.0103 97
 
0.5%
Other values (619) 4788
 
23.9%
(Missing) 13615
68.1%
ValueCountFrequency (%)
0 20
0.1%
0.0009 4
 
< 0.1%
0.0017 15
0.1%
0.0026 8
 
< 0.1%
0.0034 30
0.1%
ValueCountFrequency (%)
1 4
< 0.1%
0.9654 1
 
< 0.1%
0.8534 1
 
< 0.1%
0.7935 1
 
< 0.1%
0.7422 1
 
< 0.1%

LIVINGAREA_MEDI
Real number (ℝ)

Missing 

Distinct2822
Distinct (%)28.2%
Missing9977
Missing (%)49.9%
Infinite0
Infinite (%)0.0%
Mean0.1087965479
Minimum0
Maximum1
Zeros15
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:12.639786image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0082
Q10.046
median0.0761
Q30.12945
95-th percentile0.32444
Maximum1
Range1
Interquartile range (IQR)0.08345

Descriptive statistics

Standard deviation0.1123285953
Coefficient of variation (CV)1.032464701
Kurtosis11.87963655
Mean0.1087965479
Median Absolute Deviation (MAD)0.0395
Skewness2.830960266
Sum1090.4678
Variance0.01261771332
MonotonicityNot monotonic
2025-09-14T08:09:12.767036image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0709 21
 
0.1%
0.0522 20
 
0.1%
0.0714 19
 
0.1%
0.0706 18
 
0.1%
0.0516 18
 
0.1%
0.052 17
 
0.1%
0.0149 17
 
0.1%
0.0893 17
 
0.1%
0.068 17
 
0.1%
0.065 17
 
0.1%
Other values (2812) 9842
49.2%
(Missing) 9977
49.9%
ValueCountFrequency (%)
0 15
0.1%
0.0005 1
 
< 0.1%
0.0006 3
 
< 0.1%
0.0007 2
 
< 0.1%
0.0008 1
 
< 0.1%
ValueCountFrequency (%)
1 10
0.1%
0.9931 1
 
< 0.1%
0.9101 1
 
< 0.1%
0.9048 1
 
< 0.1%
0.8911 2
 
< 0.1%

NONLIVINGAPARTMENTS_MEDI
Real number (ℝ)

Missing  Zeros 

Distinct83
Distinct (%)1.3%
Missing13818
Missing (%)69.1%
Infinite0
Infinite (%)0.0%
Mean0.008274765448
Minimum0
Maximum1
Zeros3706
Zeros (%)18.5%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:12.870519image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.0039
95-th percentile0.0272
Maximum1
Range1
Interquartile range (IQR)0.0039

Descriptive statistics

Standard deviation0.04463497809
Coefficient of variation (CV)5.39410795
Kurtosis306.1970008
Mean0.008274765448
Median Absolute Deviation (MAD)0
Skewness16.04881103
Sum51.1546
Variance0.001992281269
MonotonicityNot monotonic
2025-09-14T08:09:12.978603image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3706
 
18.5%
0.0039 890
 
4.5%
0.0078 442
 
2.2%
0.0116 255
 
1.3%
0.0155 150
 
0.8%
0.0194 131
 
0.7%
0.0233 80
 
0.4%
0.0019 75
 
0.4%
0.0272 72
 
0.4%
0.0311 60
 
0.3%
Other values (73) 321
 
1.6%
(Missing) 13818
69.1%
ValueCountFrequency (%)
0 3706
18.5%
0.0019 75
 
0.4%
0.0039 890
 
4.5%
0.0058 32
 
0.2%
0.0078 442
 
2.2%
ValueCountFrequency (%)
1 4
< 0.1%
0.9782 1
 
< 0.1%
0.9394 1
 
< 0.1%
0.9317 1
 
< 0.1%
0.7764 1
 
< 0.1%

NONLIVINGAREA_MEDI
Real number (ℝ)

Missing  Zeros 

Distinct1399
Distinct (%)15.5%
Missing10984
Missing (%)54.9%
Infinite0
Infinite (%)0.0%
Mean0.02808785492
Minimum0
Maximum1
Zeros4001
Zeros (%)20.0%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:13.075680image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.0031
Q30.027225
95-th percentile0.124675
Maximum1
Range1
Interquartile range (IQR)0.027225

Descriptive statistics

Standard deviation0.07008370992
Coefficient of variation (CV)2.495160635
Kurtosis69.40429402
Mean0.02808785492
Median Absolute Deviation (MAD)0.0031
Skewness6.821417422
Sum253.2401
Variance0.004911726396
MonotonicityNot monotonic
2025-09-14T08:09:13.183154image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 4001
 
20.0%
0.0037 41
 
0.2%
0.0011 38
 
0.2%
0.0047 37
 
0.2%
0.0012 32
 
0.2%
0.0022 31
 
0.2%
0.0031 30
 
0.1%
0.0023 29
 
0.1%
0.0045 29
 
0.1%
0.0053 28
 
0.1%
Other values (1389) 4720
23.6%
(Missing) 10984
54.9%
ValueCountFrequency (%)
0 4001
20.0%
0.0001 12
 
0.1%
0.0002 7
 
< 0.1%
0.0003 6
 
< 0.1%
0.0004 10
 
0.1%
ValueCountFrequency (%)
1 8
< 0.1%
0.9792 1
 
< 0.1%
0.9759 2
 
< 0.1%
0.8833 1
 
< 0.1%
0.8752 1
 
< 0.1%

FONDKAPREMONT_MODE
Text

Missing 

Distinct4
Distinct (%)0.1%
Missing13615
Missing (%)68.1%
Memory size989.9 KiB
2025-09-14T08:09:13.335248image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length21
Median length16
Mean length16.464213
Min length13

Characters and Unicode

Total characters105124
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowreg oper account
2nd rowreg oper account
3rd roworg spec account
4th rowreg oper account
5th rowreg oper account
ValueCountFrequency (%)
account 6033
30.8%
reg 5662
28.9%
oper 5662
28.9%
spec 1175
 
6.0%
org 371
 
1.9%
not 352
 
1.8%
specified 352
 
1.8%
2025-09-14T08:09:13.595870image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
c 13593
12.9%
13222
12.6%
e 13203
12.6%
o 12418
11.8%
r 11695
11.1%
p 7189
6.8%
n 6385
6.1%
t 6385
6.1%
g 6033
5.7%
a 6033
5.7%
Other values (5) 8968
8.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 105124
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
c 13593
12.9%
13222
12.6%
e 13203
12.6%
o 12418
11.8%
r 11695
11.1%
p 7189
6.8%
n 6385
6.1%
t 6385
6.1%
g 6033
5.7%
a 6033
5.7%
Other values (5) 8968
8.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 105124
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
c 13593
12.9%
13222
12.6%
e 13203
12.6%
o 12418
11.8%
r 11695
11.1%
p 7189
6.8%
n 6385
6.1%
t 6385
6.1%
g 6033
5.7%
a 6033
5.7%
Other values (5) 8968
8.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 105124
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
c 13593
12.9%
13222
12.6%
e 13203
12.6%
o 12418
11.8%
r 11695
11.1%
p 7189
6.8%
n 6385
6.1%
t 6385
6.1%
g 6033
5.7%
a 6033
5.7%
Other values (5) 8968
8.5%

HOUSETYPE_MODE
Text

Missing 

Distinct3
Distinct (%)< 0.1%
Missing9968
Missing (%)49.8%
Memory size1.1 MiB
2025-09-14T08:09:13.738167image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length16
Median length14
Mean length14.02053429
Min length14

Characters and Unicode

Total characters140654
Distinct characters19
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowblock of flats
2nd rowblock of flats
3rd rowblock of flats
4th rowblock of flats
5th rowblock of flats
ValueCountFrequency (%)
block 9840
32.9%
of 9840
32.9%
flats 9840
32.9%
specific 103
 
0.3%
housing 103
 
0.3%
terraced 89
 
0.3%
house 89
 
0.3%
2025-09-14T08:09:13.992899image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 19872
14.1%
19872
14.1%
f 19783
14.1%
l 19680
14.0%
c 10135
7.2%
s 10135
7.2%
t 9929
7.1%
a 9929
7.1%
b 9840
7.0%
k 9840
7.0%
Other values (9) 1639
 
1.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 140654
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o 19872
14.1%
19872
14.1%
f 19783
14.1%
l 19680
14.0%
c 10135
7.2%
s 10135
7.2%
t 9929
7.1%
a 9929
7.1%
b 9840
7.0%
k 9840
7.0%
Other values (9) 1639
 
1.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 140654
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o 19872
14.1%
19872
14.1%
f 19783
14.1%
l 19680
14.0%
c 10135
7.2%
s 10135
7.2%
t 9929
7.1%
a 9929
7.1%
b 9840
7.0%
k 9840
7.0%
Other values (9) 1639
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 140654
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o 19872
14.1%
19872
14.1%
f 19783
14.1%
l 19680
14.0%
c 10135
7.2%
s 10135
7.2%
t 9929
7.1%
a 9929
7.1%
b 9840
7.0%
k 9840
7.0%
Other values (9) 1639
 
1.2%

TOTALAREA_MODE
Real number (ℝ)

Missing 

Distinct2787
Distinct (%)26.8%
Missing9596
Missing (%)48.0%
Infinite0
Infinite (%)0.0%
Mean0.1022919935
Minimum0
Maximum1
Zeros44
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:14.114655image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0064
Q10.0407
median0.0691
Q30.12705
95-th percentile0.3097
Maximum1
Range1
Interquartile range (IQR)0.08635

Descriptive statistics

Standard deviation0.1060367331
Coefficient of variation (CV)1.036608336
Kurtosis11.35675539
Mean0.1022919935
Median Absolute Deviation (MAD)0.0379
Skewness2.697153159
Sum1064.2459
Variance0.01124378877
MonotonicityNot monotonic
2025-09-14T08:09:14.254823image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 44
 
0.2%
0.0556 22
 
0.1%
0.0564 20
 
0.1%
0.0551 20
 
0.1%
0.0547 19
 
0.1%
0.0688 19
 
0.1%
0.0557 19
 
0.1%
0.0573 19
 
0.1%
0.0017 19
 
0.1%
0.0545 18
 
0.1%
Other values (2777) 10185
50.9%
(Missing) 9596
48.0%
ValueCountFrequency (%)
0 44
0.2%
0.0001 2
 
< 0.1%
0.0005 1
 
< 0.1%
0.0006 5
 
< 0.1%
0.0007 1
 
< 0.1%
ValueCountFrequency (%)
1 8
< 0.1%
0.956 1
 
< 0.1%
0.9486 1
 
< 0.1%
0.9214 1
 
< 0.1%
0.9057 1
 
< 0.1%

WALLSMATERIAL_MODE
Text

Missing 

Distinct7
Distinct (%)0.1%
Missing10113
Missing (%)50.6%
Memory size1023.8 KiB
2025-09-14T08:09:14.490498image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length12
Median length5
Mean length8.116314352
Min length5

Characters and Unicode

Total characters80246
Distinct characters23
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMonolithic
2nd rowPanel
3rd rowStone, brick
4th rowPanel
5th rowStone, brick
ValueCountFrequency (%)
panel 4282
30.3%
stone 4261
30.1%
brick 4261
30.1%
block 625
 
4.4%
wooden 348
 
2.5%
mixed 151
 
1.1%
others 116
 
0.8%
monolithic 104
 
0.7%
2025-09-14T08:09:14.815957image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 9158
 
11.4%
n 8995
 
11.2%
o 5790
 
7.2%
l 5011
 
6.2%
c 4990
 
6.2%
k 4886
 
6.1%
i 4620
 
5.8%
t 4481
 
5.6%
r 4377
 
5.5%
P 4282
 
5.3%
Other values (13) 23656
29.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 80246
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 9158
 
11.4%
n 8995
 
11.2%
o 5790
 
7.2%
l 5011
 
6.2%
c 4990
 
6.2%
k 4886
 
6.1%
i 4620
 
5.8%
t 4481
 
5.6%
r 4377
 
5.5%
P 4282
 
5.3%
Other values (13) 23656
29.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 80246
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 9158
 
11.4%
n 8995
 
11.2%
o 5790
 
7.2%
l 5011
 
6.2%
c 4990
 
6.2%
k 4886
 
6.1%
i 4620
 
5.8%
t 4481
 
5.6%
r 4377
 
5.5%
P 4282
 
5.3%
Other values (13) 23656
29.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 80246
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 9158
 
11.4%
n 8995
 
11.2%
o 5790
 
7.2%
l 5011
 
6.2%
c 4990
 
6.2%
k 4886
 
6.1%
i 4620
 
5.8%
t 4481
 
5.6%
r 4377
 
5.5%
P 4282
 
5.3%
Other values (13) 23656
29.5%

EMERGENCYSTATE_MODE
Text

Missing 

Distinct2
Distinct (%)< 0.1%
Missing9411
Missing (%)47.1%
Memory size977.9 KiB
2025-09-14T08:09:14.881070image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.014165644
Min length2

Characters and Unicode

Total characters21328
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 10439
98.6%
yes 150
 
1.4%
2025-09-14T08:09:15.022232image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 10439
48.9%
o 10439
48.9%
Y 150
 
0.7%
e 150
 
0.7%
s 150
 
0.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 21328
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
N 10439
48.9%
o 10439
48.9%
Y 150
 
0.7%
e 150
 
0.7%
s 150
 
0.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 21328
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
N 10439
48.9%
o 10439
48.9%
Y 150
 
0.7%
e 150
 
0.7%
s 150
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 21328
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
N 10439
48.9%
o 10439
48.9%
Y 150
 
0.7%
e 150
 
0.7%
s 150
 
0.7%

OBS_30_CNT_SOCIAL_CIRCLE
Real number (ℝ)

Zeros 

Distinct25
Distinct (%)0.1%
Missing71
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean1.428671785
Minimum0
Maximum25
Zeros10690
Zeros (%)53.4%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:15.107659image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile6
Maximum25
Range25
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.346842658
Coefficient of variation (CV)1.642674464
Kurtosis9.949757718
Mean1.428671785
Median Absolute Deviation (MAD)0
Skewness2.615693495
Sum28472
Variance5.507670461
MonotonicityNot monotonic
2025-09-14T08:09:15.226686image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
0 10690
53.4%
1 3153
 
15.8%
2 1934
 
9.7%
3 1278
 
6.4%
4 922
 
4.6%
5 640
 
3.2%
6 422
 
2.1%
7 272
 
1.4%
8 189
 
0.9%
9 140
 
0.7%
Other values (15) 289
 
1.4%
ValueCountFrequency (%)
0 10690
53.4%
1 3153
 
15.8%
2 1934
 
9.7%
3 1278
 
6.4%
4 922
 
4.6%
ValueCountFrequency (%)
25 3
< 0.1%
23 1
 
< 0.1%
22 3
< 0.1%
21 3
< 0.1%
20 1
 
< 0.1%

DEF_30_CNT_SOCIAL_CIRCLE
Real number (ℝ)

Zeros 

Distinct7
Distinct (%)< 0.1%
Missing71
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean0.1444628431
Minimum0
Maximum6
Zeros17625
Zeros (%)88.1%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:15.307373image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum6
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.4445966396
Coefficient of variation (CV)3.077584728
Kurtosis19.48914879
Mean0.1444628431
Median Absolute Deviation (MAD)0
Skewness3.869361749
Sum2879
Variance0.197666172
MonotonicityNot monotonic
2025-09-14T08:09:15.379959image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 17625
88.1%
1 1858
 
9.3%
2 344
 
1.7%
3 80
 
0.4%
4 19
 
0.1%
6 2
 
< 0.1%
5 1
 
< 0.1%
(Missing) 71
 
0.4%
ValueCountFrequency (%)
0 17625
88.1%
1 1858
 
9.3%
2 344
 
1.7%
3 80
 
0.4%
4 19
 
0.1%
ValueCountFrequency (%)
6 2
 
< 0.1%
5 1
 
< 0.1%
4 19
 
0.1%
3 80
 
0.4%
2 344
1.7%

OBS_60_CNT_SOCIAL_CIRCLE
Real number (ℝ)

Zeros 

Distinct25
Distinct (%)0.1%
Missing71
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean1.412012645
Minimum0
Maximum25
Zeros10742
Zeros (%)53.7%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:15.651696image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile6
Maximum25
Range25
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.326344983
Coefficient of variation (CV)1.64753835
Kurtosis9.913950324
Mean1.412012645
Median Absolute Deviation (MAD)0
Skewness2.61679122
Sum28140
Variance5.41188098
MonotonicityNot monotonic
2025-09-14T08:09:15.758482image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
0 10742
53.7%
1 3156
 
15.8%
2 1921
 
9.6%
3 1285
 
6.4%
4 903
 
4.5%
5 631
 
3.2%
6 420
 
2.1%
7 271
 
1.4%
8 183
 
0.9%
9 138
 
0.7%
Other values (15) 279
 
1.4%
ValueCountFrequency (%)
0 10742
53.7%
1 3156
 
15.8%
2 1921
 
9.6%
3 1285
 
6.4%
4 903
 
4.5%
ValueCountFrequency (%)
25 2
< 0.1%
24 1
 
< 0.1%
22 3
< 0.1%
21 3
< 0.1%
20 2
< 0.1%

DEF_60_CNT_SOCIAL_CIRCLE
Real number (ℝ)

Zeros 

Distinct6
Distinct (%)< 0.1%
Missing71
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean0.1016608962
Minimum0
Maximum5
Zeros18223
Zeros (%)91.1%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:15.836173image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum5
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.3625948999
Coefficient of variation (CV)3.566709655
Kurtosis24.61468385
Mean0.1016608962
Median Absolute Deviation (MAD)0
Skewness4.389857735
Sum2026
Variance0.1314750614
MonotonicityNot monotonic
2025-09-14T08:09:15.909302image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 18223
91.1%
1 1453
 
7.3%
2 198
 
1.0%
3 44
 
0.2%
4 10
 
0.1%
5 1
 
< 0.1%
(Missing) 71
 
0.4%
ValueCountFrequency (%)
0 18223
91.1%
1 1453
 
7.3%
2 198
 
1.0%
3 44
 
0.2%
4 10
 
0.1%
ValueCountFrequency (%)
5 1
 
< 0.1%
4 10
 
0.1%
3 44
 
0.2%
2 198
 
1.0%
1 1453
7.3%

DAYS_LAST_PHONE_CHANGE
Real number (ℝ)

Zeros 

Distinct3080
Distinct (%)15.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-959.06045
Minimum-4066
Maximum0
Zeros2477
Zeros (%)12.4%
Negative17523
Negative (%)87.6%
Memory size312.5 KiB
2025-09-14T08:09:15.999998image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-4066
5-th percentile-2519.05
Q1-1569.25
median-746
Q3-269
95-th percentile0
Maximum0
Range4066
Interquartile range (IQR)1300.25

Descriptive statistics

Standard deviation826.6820857
Coefficient of variation (CV)-0.8619707816
Kurtosis-0.3273029821
Mean-959.06045
Median Absolute Deviation (MAD)635
Skewness-0.7110813348
Sum-19181209
Variance683403.2709
MonotonicityNot monotonic
2025-09-14T08:09:16.109442image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2477
 
12.4%
-1 195
 
1.0%
-2 163
 
0.8%
-3 121
 
0.6%
-4 76
 
0.4%
-5 60
 
0.3%
-6 34
 
0.2%
-7 33
 
0.2%
-11 24
 
0.1%
-239 23
 
0.1%
Other values (3070) 16794
84.0%
ValueCountFrequency (%)
-4066 1
< 0.1%
-4051 1
< 0.1%
-4039 1
< 0.1%
-3939 1
< 0.1%
-3793 1
< 0.1%
ValueCountFrequency (%)
0 2477
12.4%
-1 195
 
1.0%
-2 163
 
0.8%
-3 121
 
0.6%
-4 76
 
0.4%

FLAG_DOCUMENT_2
Real number (ℝ)

Skewed  Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0002
Minimum0
Maximum1
Zeros19996
Zeros (%)> 99.9%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:16.185779image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.01414107487
Coefficient of variation (CV)70.70537435
Kurtosis4996.249475
Mean0.0002
Median Absolute Deviation (MAD)0
Skewness70.69476537
Sum4
Variance0.0001999699985
MonotonicityNot monotonic
2025-09-14T08:09:16.241781image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 19996
> 99.9%
1 4
 
< 0.1%
ValueCountFrequency (%)
0 19996
> 99.9%
1 4
 
< 0.1%
ValueCountFrequency (%)
1 4
 
< 0.1%
0 19996
> 99.9%

FLAG_DOCUMENT_3
Real number (ℝ)

Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.7085
Minimum0
Maximum1
Zeros5830
Zeros (%)29.1%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:16.301040image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.4544646047
Coefficient of variation (CV)0.6414461604
Kurtosis-1.158025165
Mean0.7085
Median Absolute Deviation (MAD)0
Skewness-0.9176549722
Sum14170
Variance0.2065380769
MonotonicityNot monotonic
2025-09-14T08:09:16.361036image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
1 14170
70.9%
0 5830
29.1%
ValueCountFrequency (%)
0 5830
29.1%
1 14170
70.9%
ValueCountFrequency (%)
1 14170
70.9%
0 5830
29.1%

FLAG_DOCUMENT_4
Real number (ℝ)

Skewed  Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0001
Minimum0
Maximum1
Zeros19998
Zeros (%)> 99.9%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:16.420593image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.009999749984
Coefficient of variation (CV)99.99749984
Kurtosis9997.4996
Mean0.0001
Median Absolute Deviation (MAD)0
Skewness99.99249897
Sum2
Variance9.999499975 × 10-5
MonotonicityNot monotonic
2025-09-14T08:09:16.478166image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 19998
> 99.9%
1 2
 
< 0.1%
ValueCountFrequency (%)
0 19998
> 99.9%
1 2
 
< 0.1%
ValueCountFrequency (%)
1 2
 
< 0.1%
0 19998
> 99.9%

FLAG_DOCUMENT_5
Real number (ℝ)

Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.01395
Minimum0
Maximum1
Zeros19721
Zeros (%)98.6%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:16.531130image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.1172863389
Coefficient of variation (CV)8.407622864
Kurtosis66.71571291
Mean0.01395
Median Absolute Deviation (MAD)0
Skewness8.289091709
Sum279
Variance0.0137560853
MonotonicityNot monotonic
2025-09-14T08:09:16.586031image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 19721
98.6%
1 279
 
1.4%
ValueCountFrequency (%)
0 19721
98.6%
1 279
 
1.4%
ValueCountFrequency (%)
1 279
 
1.4%
0 19721
98.6%

FLAG_DOCUMENT_6
Real number (ℝ)

Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.08775
Minimum0
Maximum1
Zeros18245
Zeros (%)91.2%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:16.649132image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.2829380501
Coefficient of variation (CV)3.224365243
Kurtosis6.494125536
Mean0.08775
Median Absolute Deviation (MAD)0
Skewness2.914356899
Sum1755
Variance0.0800539402
MonotonicityNot monotonic
2025-09-14T08:09:16.727244image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 18245
91.2%
1 1755
 
8.8%
ValueCountFrequency (%)
0 18245
91.2%
1 1755
 
8.8%
ValueCountFrequency (%)
1 1755
 
8.8%
0 18245
91.2%

FLAG_DOCUMENT_7
Real number (ℝ)

Skewed  Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.00015
Minimum0
Maximum1
Zeros19997
Zeros (%)> 99.9%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:16.793679image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.0122468363
Coefficient of variation (CV)81.6455753
Kurtosis6663.332833
Mean0.00015
Median Absolute Deviation (MAD)0
Skewness81.6374087
Sum3
Variance0.0001499849992
MonotonicityNot monotonic
2025-09-14T08:09:16.859428image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 19997
> 99.9%
1 3
 
< 0.1%
ValueCountFrequency (%)
0 19997
> 99.9%
1 3
 
< 0.1%
ValueCountFrequency (%)
1 3
 
< 0.1%
0 19997
> 99.9%

FLAG_DOCUMENT_8
Real number (ℝ)

Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.08345
Minimum0
Maximum1
Zeros18331
Zeros (%)91.7%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:16.925689image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.2765681146
Coefficient of variation (CV)3.314177526
Kurtosis7.076340385
Mean0.08345
Median Absolute Deviation (MAD)0
Skewness3.012579088
Sum1669
Variance0.076489922
MonotonicityNot monotonic
2025-09-14T08:09:16.987342image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 18331
91.7%
1 1669
 
8.3%
ValueCountFrequency (%)
0 18331
91.7%
1 1669
 
8.3%
ValueCountFrequency (%)
1 1669
 
8.3%
0 18331
91.7%

FLAG_DOCUMENT_9
Real number (ℝ)

Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0042
Minimum0
Maximum1
Zeros19916
Zeros (%)99.6%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:17.052340image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.06467278507
Coefficient of variation (CV)15.39828216
Kurtosis233.1580412
Mean0.0042
Median Absolute Deviation (MAD)0
Skewness15.33410335
Sum84
Variance0.004182569128
MonotonicityNot monotonic
2025-09-14T08:09:17.108903image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 19916
99.6%
1 84
 
0.4%
ValueCountFrequency (%)
0 19916
99.6%
1 84
 
0.4%
ValueCountFrequency (%)
1 84
 
0.4%
0 19916
99.6%

FLAG_DOCUMENT_10
Real number (ℝ)

Constant  Zeros 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros20000
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:17.154912image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2025-09-14T08:09:17.211469image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 20000
100.0%
ValueCountFrequency (%)
0 20000
100.0%
ValueCountFrequency (%)
0 20000
100.0%

FLAG_DOCUMENT_11
Real number (ℝ)

Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.00455
Minimum0
Maximum1
Zeros19909
Zeros (%)99.5%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:17.266056image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.06730173829
Coefficient of variation (CV)14.79159083
Kurtosis214.8387965
Mean0.00455
Median Absolute Deviation (MAD)0
Skewness14.72471774
Sum91
Variance0.004529523976
MonotonicityNot monotonic
2025-09-14T08:09:17.329602image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 19909
99.5%
1 91
 
0.5%
ValueCountFrequency (%)
0 19909
99.5%
1 91
 
0.5%
ValueCountFrequency (%)
1 91
 
0.5%
0 19909
99.5%

FLAG_DOCUMENT_12
Real number (ℝ)

Skewed  Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5 × 10-5
Minimum0
Maximum1
Zeros19999
Zeros (%)> 99.9%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:17.389725image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.007071067812
Coefficient of variation (CV)141.4213562
Kurtosis20000
Mean5 × 10-5
Median Absolute Deviation (MAD)0
Skewness141.4213562
Sum1
Variance5 × 10-5
MonotonicityNot monotonic
2025-09-14T08:09:17.448730image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 19999
> 99.9%
1 1
 
< 0.1%
ValueCountFrequency (%)
0 19999
> 99.9%
1 1
 
< 0.1%
ValueCountFrequency (%)
1 1
 
< 0.1%
0 19999
> 99.9%

FLAG_DOCUMENT_13
Real number (ℝ)

Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0036
Minimum0
Maximum1
Zeros19928
Zeros (%)99.6%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:17.507952image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.05989339998
Coefficient of variation (CV)16.63705555
Kurtosis272.8498985
Mean0.0036
Median Absolute Deviation (MAD)0
Skewness16.57777468
Sum72
Variance0.003587219361
MonotonicityNot monotonic
2025-09-14T08:09:17.575159image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 19928
99.6%
1 72
 
0.4%
ValueCountFrequency (%)
0 19928
99.6%
1 72
 
0.4%
ValueCountFrequency (%)
1 72
 
0.4%
0 19928
99.6%

FLAG_DOCUMENT_14
Real number (ℝ)

Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0031
Minimum0
Maximum1
Zeros19938
Zeros (%)99.7%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:17.641873image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.05559266613
Coefficient of variation (CV)17.93311811
Kurtosis317.6634651
Mean0.0031
Median Absolute Deviation (MAD)0
Skewness17.87824652
Sum62
Variance0.003090544527
MonotonicityNot monotonic
2025-09-14T08:09:17.718549image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 19938
99.7%
1 62
 
0.3%
ValueCountFrequency (%)
0 19938
99.7%
1 62
 
0.3%
ValueCountFrequency (%)
1 62
 
0.3%
0 19938
99.7%

FLAG_DOCUMENT_15
Real number (ℝ)

Skewed  Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0017
Minimum0
Maximum1
Zeros19966
Zeros (%)99.8%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:17.772463image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.04119702489
Coefficient of variation (CV)24.23354405
Kurtosis583.3831326
Mean0.0017
Median Absolute Deviation (MAD)0
Skewness24.19348661
Sum34
Variance0.00169719486
MonotonicityNot monotonic
2025-09-14T08:09:17.841055image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 19966
99.8%
1 34
 
0.2%
ValueCountFrequency (%)
0 19966
99.8%
1 34
 
0.2%
ValueCountFrequency (%)
1 34
 
0.2%
0 19966
99.8%

FLAG_DOCUMENT_16
Real number (ℝ)

Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0106
Minimum0
Maximum1
Zeros19788
Zeros (%)98.9%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:17.902658image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.1024117396
Coefficient of variation (CV)9.661484868
Kurtosis89.37297787
Mean0.0106
Median Absolute Deviation (MAD)0
Skewness9.55845388
Sum212
Variance0.01048816441
MonotonicityNot monotonic
2025-09-14T08:09:17.962573image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 19788
98.9%
1 212
 
1.1%
ValueCountFrequency (%)
0 19788
98.9%
1 212
 
1.1%
ValueCountFrequency (%)
1 212
 
1.1%
0 19788
98.9%

FLAG_DOCUMENT_17
Real number (ℝ)

Skewed  Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0004
Minimum0
Maximum1
Zeros19992
Zeros (%)> 99.9%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:18.025172image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.01999649952
Coefficient of variation (CV)49.9912488
Kurtosis2495.624563
Mean0.0004
Median Absolute Deviation (MAD)0
Skewness49.97374311
Sum8
Variance0.000399859993
MonotonicityNot monotonic
2025-09-14T08:09:18.077178image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 19992
> 99.9%
1 8
 
< 0.1%
ValueCountFrequency (%)
0 19992
> 99.9%
1 8
 
< 0.1%
ValueCountFrequency (%)
1 8
 
< 0.1%
0 19992
> 99.9%

FLAG_DOCUMENT_18
Real number (ℝ)

Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0082
Minimum0
Maximum1
Zeros19836
Zeros (%)99.2%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:18.146476image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.09018407098
Coefficient of variation (CV)10.99805744
Kurtosis116.9890325
Mean0.0082
Median Absolute Deviation (MAD)0
Skewness10.90767315
Sum164
Variance0.008133166658
MonotonicityNot monotonic
2025-09-14T08:09:18.205109image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 19836
99.2%
1 164
 
0.8%
ValueCountFrequency (%)
0 19836
99.2%
1 164
 
0.8%
ValueCountFrequency (%)
1 164
 
0.8%
0 19836
99.2%

FLAG_DOCUMENT_19
Real number (ℝ)

Skewed  Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0007
Minimum0
Maximum1
Zeros19986
Zeros (%)99.9%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:18.261113image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.02644891259
Coefficient of variation (CV)37.78416084
Kurtosis1423.928386
Mean0.0007
Median Absolute Deviation (MAD)0
Skewness37.75958148
Sum14
Variance0.0006995449772
MonotonicityNot monotonic
2025-09-14T08:09:18.321078image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 19986
99.9%
1 14
 
0.1%
ValueCountFrequency (%)
0 19986
99.9%
1 14
 
0.1%
ValueCountFrequency (%)
1 14
 
0.1%
0 19986
99.9%

FLAG_DOCUMENT_20
Real number (ℝ)

Skewed  Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.00065
Minimum0
Maximum1
Zeros19987
Zeros (%)99.9%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:18.383915image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.02548744751
Coefficient of variation (CV)39.21145771
Kurtosis1533.845924
Mean0.00065
Median Absolute Deviation (MAD)0
Skewness39.18791317
Sum13
Variance0.0006496099805
MonotonicityNot monotonic
2025-09-14T08:09:18.437912image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 19987
99.9%
1 13
 
0.1%
ValueCountFrequency (%)
0 19987
99.9%
1 13
 
0.1%
ValueCountFrequency (%)
1 13
 
0.1%
0 19987
99.9%

FLAG_DOCUMENT_21
Real number (ℝ)

Skewed  Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.00045
Minimum0
Maximum1
Zeros19991
Zeros (%)> 99.9%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:18.504926image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.02120896016
Coefficient of variation (CV)47.13102257
Kurtosis2217.777378
Mean0.00045
Median Absolute Deviation (MAD)0
Skewness47.11215979
Sum9
Variance0.000449819991
MonotonicityNot monotonic
2025-09-14T08:09:18.556794image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 19991
> 99.9%
1 9
 
< 0.1%
ValueCountFrequency (%)
0 19991
> 99.9%
1 9
 
< 0.1%
ValueCountFrequency (%)
1 9
 
< 0.1%
0 19991
> 99.9%

AMT_REQ_CREDIT_BUREAU_HOUR
Real number (ℝ)

Missing  Zeros 

Distinct5
Distinct (%)< 0.1%
Missing2647
Missing (%)13.2%
Infinite0
Infinite (%)0.0%
Mean0.006915230796
Minimum0
Maximum4
Zeros17240
Zeros (%)86.2%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:18.616225image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum4
Range4
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.09019795743
Coefficient of variation (CV)13.04337629
Kurtosis408.1647455
Mean0.006915230796
Median Absolute Deviation (MAD)0
Skewness16.73492319
Sum120
Variance0.008135671525
MonotonicityNot monotonic
2025-09-14T08:09:18.691054image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%)
0 17240
86.2%
1 109
 
0.5%
2 2
 
< 0.1%
4 1
 
< 0.1%
3 1
 
< 0.1%
(Missing) 2647
 
13.2%
ValueCountFrequency (%)
0 17240
86.2%
1 109
 
0.5%
2 2
 
< 0.1%
3 1
 
< 0.1%
4 1
 
< 0.1%
ValueCountFrequency (%)
4 1
 
< 0.1%
3 1
 
< 0.1%
2 2
 
< 0.1%
1 109
 
0.5%
0 17240
86.2%

AMT_REQ_CREDIT_BUREAU_DAY
Real number (ℝ)

Missing  Skewed  Zeros 

Distinct8
Distinct (%)< 0.1%
Missing2647
Missing (%)13.2%
Infinite0
Infinite (%)0.0%
Mean0.009277934651
Minimum0
Maximum8
Zeros17237
Zeros (%)86.2%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:18.773404image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum8
Range8
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.1451351599
Coefficient of variation (CV)15.64304615
Kurtosis1026.191801
Mean0.009277934651
Median Absolute Deviation (MAD)0
Skewness27.27689465
Sum161
Variance0.02106421465
MonotonicityNot monotonic
2025-09-14T08:09:18.844186image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 17237
86.2%
1 99
 
0.5%
4 6
 
< 0.1%
2 5
 
< 0.1%
3 3
 
< 0.1%
5 1
 
< 0.1%
8 1
 
< 0.1%
6 1
 
< 0.1%
(Missing) 2647
 
13.2%
ValueCountFrequency (%)
0 17237
86.2%
1 99
 
0.5%
2 5
 
< 0.1%
3 3
 
< 0.1%
4 6
 
< 0.1%
ValueCountFrequency (%)
8 1
 
< 0.1%
6 1
 
< 0.1%
5 1
 
< 0.1%
4 6
< 0.1%
3 3
< 0.1%

AMT_REQ_CREDIT_BUREAU_WEEK
Real number (ℝ)

Missing  Zeros 

Distinct7
Distinct (%)< 0.1%
Missing2647
Missing (%)13.2%
Infinite0
Infinite (%)0.0%
Mean0.03434564629
Minimum0
Maximum6
Zeros16794
Zeros (%)84.0%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:18.928879image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum6
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.2030669063
Coefficient of variation (CV)5.912449707
Kurtosis133.0555618
Mean0.03434564629
Median Absolute Deviation (MAD)0
Skewness8.711030796
Sum596
Variance0.04123616844
MonotonicityNot monotonic
2025-09-14T08:09:18.998602image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 16794
84.0%
1 540
 
2.7%
2 11
 
0.1%
4 3
 
< 0.1%
3 2
 
< 0.1%
5 2
 
< 0.1%
6 1
 
< 0.1%
(Missing) 2647
 
13.2%
ValueCountFrequency (%)
0 16794
84.0%
1 540
 
2.7%
2 11
 
0.1%
3 2
 
< 0.1%
4 3
 
< 0.1%
ValueCountFrequency (%)
6 1
 
< 0.1%
5 2
 
< 0.1%
4 3
 
< 0.1%
3 2
 
< 0.1%
2 11
0.1%

AMT_REQ_CREDIT_BUREAU_MON
Real number (ℝ)

Missing  Zeros 

Distinct18
Distinct (%)0.1%
Missing2647
Missing (%)13.2%
Infinite0
Infinite (%)0.0%
Mean0.2717685703
Minimum0
Maximum17
Zeros14440
Zeros (%)72.2%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:19.070623image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum17
Range17
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.9130710136
Coefficient of variation (CV)3.359737341
Kurtosis78.04642253
Mean0.2717685703
Median Absolute Deviation (MAD)0
Skewness7.348768895
Sum4716
Variance0.8336986758
MonotonicityNot monotonic
2025-09-14T08:09:19.155655image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0 14440
72.2%
1 2228
 
11.1%
2 339
 
1.7%
3 122
 
0.6%
4 74
 
0.4%
5 39
 
0.2%
7 30
 
0.1%
6 22
 
0.1%
10 15
 
0.1%
8 13
 
0.1%
Other values (8) 31
 
0.2%
(Missing) 2647
 
13.2%
ValueCountFrequency (%)
0 14440
72.2%
1 2228
 
11.1%
2 339
 
1.7%
3 122
 
0.6%
4 74
 
0.4%
ValueCountFrequency (%)
17 2
< 0.1%
16 1
 
< 0.1%
15 1
 
< 0.1%
14 4
< 0.1%
13 3
< 0.1%

AMT_REQ_CREDIT_BUREAU_QRT
Real number (ℝ)

Missing  Zeros 

Distinct7
Distinct (%)< 0.1%
Missing2647
Missing (%)13.2%
Infinite0
Infinite (%)0.0%
Mean0.257707601
Minimum0
Maximum6
Zeros14123
Zeros (%)70.6%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:19.230306image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum6
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.6021482408
Coefficient of variation (CV)2.336555998
Kurtosis8.034824989
Mean0.257707601
Median Absolute Deviation (MAD)0
Skewness2.658098929
Sum4472
Variance0.3625825039
MonotonicityNot monotonic
2025-09-14T08:09:19.298829image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 14123
70.6%
1 2180
 
10.9%
2 900
 
4.5%
3 117
 
0.6%
4 25
 
0.1%
5 7
 
< 0.1%
6 1
 
< 0.1%
(Missing) 2647
 
13.2%
ValueCountFrequency (%)
0 14123
70.6%
1 2180
 
10.9%
2 900
 
4.5%
3 117
 
0.6%
4 25
 
0.1%
ValueCountFrequency (%)
6 1
 
< 0.1%
5 7
 
< 0.1%
4 25
 
0.1%
3 117
 
0.6%
2 900
4.5%

AMT_REQ_CREDIT_BUREAU_YEAR
Real number (ℝ)

Missing  Zeros 

Distinct16
Distinct (%)0.1%
Missing2647
Missing (%)13.2%
Infinite0
Infinite (%)0.0%
Mean1.868264853
Minimum0
Maximum22
Zeros4823
Zeros (%)24.1%
Negative0
Negative (%)0.0%
Memory size312.5 KiB
2025-09-14T08:09:19.362822image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q33
95-th percentile6
Maximum22
Range22
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.863897952
Coefficient of variation (CV)0.9976625897
Kurtosis2.712787215
Mean1.868264853
Median Absolute Deviation (MAD)1
Skewness1.313629109
Sum32420
Variance3.474115575
MonotonicityNot monotonic
2025-09-14T08:09:19.438293image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
0 4823
24.1%
1 4124
20.6%
2 3276
16.4%
3 2140
10.7%
4 1294
 
6.5%
5 804
 
4.0%
6 449
 
2.2%
7 233
 
1.2%
8 134
 
0.7%
9 67
 
0.3%
Other values (6) 9
 
< 0.1%
(Missing) 2647
13.2%
ValueCountFrequency (%)
0 4823
24.1%
1 4124
20.6%
2 3276
16.4%
3 2140
10.7%
4 1294
 
6.5%
ValueCountFrequency (%)
22 1
< 0.1%
18 1
< 0.1%
17 2
< 0.1%
13 1
< 0.1%
11 1
< 0.1%